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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role You will own the documentation for Claude apps . This role goes far beyond traditional technical writing. The docs estate of Claude Docs spans multiple product surfaces ( Claude.ai , Cowork, Claude Tag, Claude Science, etc.) written by many hands across many teams. You'll own the unification layer: the architecture, the standards, and — centrally — the engineered systems that keep quality high at scale. This is a content + systems ownership role. You'll curate and set the bar for what others write, and you'll build the automation that enforces it: self-healing pipelines, AI-assisted review and maintenance, and the conventions each product team follows to keep their own docs healthy. You'll work alongside the engineers building our docs tooling today. About Anthropic Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and for society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business, and product. Key responsibilities Own the information architecture, style, and editorial standards of the Claude Docs site as a single unified surface Design, build, and run automated documentation systems: self-healing pipelines, AI-assisted review and maintenance, and quality guardrails that catch problems before readers do Establish the conventions and tooling product teams adopt to keep their own documentation accurate and consistent Establish and maintain the style guide, a standard set of content types, and clear workflows for creating, reviewing, and publishing documentation Curate contributions from across the company: edit for clarity and consistency, prune what's stale, and shape how new content fits the whole Define and track measures of content quality and discoverability, and use reader feedback and analytics to drive improvements You may be a good fit if you have 5+ years at the intersection of documentation, user education, and software engineering Knowledge of evaluation frameworks or observability for AI-powered systems Experience guiding a documentation platform migration or redesign Content analytics and experimentation experience Modern software development practices: version control, CI/CD, testing Excellent technical writing and editing — enough craft to set and standardize a high quality bar Experience establishing editorial standards and information architecture for a substantial technical documentation site Strong candidates may also have Software engineering experience: you can design, build, ship, and maintain production tooling, with proficiency in Python and/or TypeScript/JavaScript Experience building automated documentation or content systems — pipelines, CI checks, AI-assisted maintenance Experience building AI applications or AI-powered tooling with LLMs The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for an Engineering Manager to lead the Search Platform team. This team builds the search stack behind Claude: the indexes, retrieval and ranking systems and serving infrastructure that power web search across claude.ai , the API and agentic surfaces. Search is core to how Claude answers questions about the world, and the team owns both the problem and the solution end to end: growing the index, improving retrieval quality and running the serving stack at production scale. The same platform also serves research workloads, so demand comes from multiple user surfaces, often at the same time. The role carries a product dimension. Search sits close to the user experience and PM coverage is thin at times, so often the EM helps decide what a good search experience looks like, not just how to build it. You'll partner with product teams shipping search-backed features, research teams that depend on retrieval quality and capacity, and the infrastructure teams that run the systems underneath. We're looking for someone with real search experience who can be hands-on when needed: reviewing designs, digging into relevance regressions and holding their own in technical debates. Key Responsibilities Lead and grow the team of engineers building Anthropic's search platform: indexing, retrieval, ranking and serving Own the strategy and roadmap for the platform and how Claude's search needs are met over time Own search quality: evaluation methodology, relevance measurement, regression detection and the ranking improvements they drive Operate the platform at scale, balancing product traffic against research and training demand while holding a high bar on reliability, latency and cost Wear the product hat when the work calls for it: prioritize what the search experience needs, sequence launches and represent search in product discussions Drive cross-team collaboration with product, research and infrastructure partners; articulate dependencies, risks and progress clearly Be hands-on where it matters: design reviews, incident follow-ups and the occasional deep dive into why relevance moved Recruit, close and retain strong engineers in a competitive market Minimum Qualifications Significant experience managing engineering teams, including hiring and growing a team through rapid change Direct experience building or operating search systems at scale: indexing, retrieval, ranking or query serving Enough technical depth to be hands-on when needed; you can review designs, read code and engage credibly with senior ICs A product mindset and comfort making product calls when there isn't a PM in the room A track record of running high-scale, latency-sensitive production systems with real reliability requirements Strong cross-functional skills; you can align product, research and infrastructure partners with different priorities Experience recruiting and closing senior engineers Interest in AI safety and Anthropic's mission Preferred Qualifications Experience with the economics of search: index freshness, storage and serving costs, quality vs cost tradeoffs Background in embeddings, ranking models or ML-based retrieval Experience migrating traffic off a vendor onto in-house infrastructure Exposure to LLM products and the retrieval demands of large-scale training and inference The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Foragers is a new Field Services team within our physical infrastructure organization. We're the boots on the ground for Anthropic's physical infrastructure: the people who get hardware into racks, gear commissioned, and sites handed over. The team is being stood up now, so early hires shape how we operate. This role is the lab-focused counterpart to our traveling field engineers. Instead of covering sites across the country, you own our Bay Area hardware labs from end to end. About the Role Your mission is to ensure our hardware labs are functional, useful, and ready to support the growing number of teams and projects that need access to physical hardware. You’d own what shows up, how it’s powered, cooled, cabled, tracked, set up, and made functional. This includes both standard hardware (think typical accelerator setups) and more specialized ones like ensuring our security teams have access to all the right headers and other hardware instrumentation on the machines. Understanding and anticipating the needs of the various teams that rely on the labs will be another critical part of this role. You’ll be expected to take a lot of ownership and initiative over the lab and what’s in it, including reaching out to partner teams to figure out what they’d need in the future and making sure it’s there before it starts to block them. This will require you to collaborate closely with those partner teams, so a breadth of knowledge around hardware is extremely useful. You’d be the first dedicated lab manager, so part of this role will include shaping it to scale from our current lab to much larger ones. What You’ll Do Run the physical lab across both sites: receiving and staging, rack-and-stack, cabling, power distribution and load planning, cooling, floor layout Bring up new server and accelerator platforms as they arrive, from crate to a machine someone can SSH into: firmware and BIOS/UEFI setup, out-of-band management, OS install, network provisioning Own hardware procurement for the lab: work with teams on what's coming, order ahead of need, chase quotes and lead times, keep receiving and inventory in order Own RMA processes end-to-end for lab hardware: triage, swap, ship, track, close; drive vendor escalations Build the one-off setups engineers ask for: debug and programming harnesses (JTAG/SWD/UART), remote power switching, console and KVM access, and the occasional improvised fix for hardware running outside the conditions it was designed for Oversee smarthands and contractor work on-site (electricians, cabling crews, riggers, integrators, OEM field engineers): scope it, dispatch it, validate the quality Handle physical access, asset auditing, and lifecycle tracking for hardware that is expensive and sometimes pre-release Write it down: build the playbooks and lightweight tooling (inventory, remote power, console access) so remote teams can use the lab without pinging you for every step Who You Are Hands-on experience running a hardware, systems, or datacenter lab, or a similar physical compute environment: rack-and-stack, copper and fiber cabling, power distribution (PDUs, circuits, phase balancing) Working knowledge of server hardware and its management plane: BMC/IPMI/Redfish, BIOS/UEFI configuration, serial console, PXE/network boot, firmware updates Enough Linux and networking (VLANs, DHCP, DNS, basic switch config) to take a bare machine to a state a remote engineer can use Have managed vendors, contractors, quotes, and freight for physical equipment Comfortable and safe with power tools, bench power supplies, and a wiring or rack elevation diagram Work independently with minimal supervision , and know when to ask Bias toward action and comfort with ambiguity: you'd rather move and adjust than wait for perfect information Communicate clearly and directly, especially when flagging risks or blockers Strong Candidates May Also Have Stood up a lab or datacenter room from empty: layout, power and cooling budget, first round of purchasing Time around high-density accelerator systems (GPU/TPU-class racks), liquid cooling, or pre-release/NPI hardware bring-up Electronics bench skills: soldering and rework, scope and multimeter, custom cable and debug harnesses, JTAG probes, light fabrication (3D printing, drilling, mounting) Supported hardware security, firmware, or platform bring-up work Experience with DCIM or asset-management tooling (NetBox, ServiceNow, etc.) Bought hard-to-source or specialty hardware and dealt with the compliance and logistics that come with it Location This role is based in our San Francisco office (500 Howard St). Travel to nearby lab spaces is required so expect to be in-office more frequently than Anthropic's standard 25% hybrid baseline. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role GTM Systems builds and operates the platform Anthropic's sales and partner teams run on: Salesforce as the core, plus the lead, marketplace, integration, and AI tooling that connect to it. The team is organized into experience pods, each owning one stage of the seller and partner journey. We're hiring a Technical Program Manager to own program delivery for the GTM systems portfolio. You'll drive roadmap execution, manage the dependencies spanning the seller and partner journey, from lead capture and routing through the core selling motion to marketplace and co-sell tooling, Responsibilities Own delivery for your program area's roadmap: intake, prioritization, sequencing, status, and the operating cadence Manage your program's dependencies on the shared GTM platform Partner with Business Systems Analysts on requirements and design, and with developers on technical tradeoffs, build-vs-buy calls, and vendor evaluation Help build the operating model for a team that's scaling: intake, planning, and sequencing practices that hold up as the portfolio grows Give GTM Systems and Sales leadership a clear view of your program's commitments, risks, and progress Help bring Claude into the GTM workflow where it makes sellers and partner managers faster You may be a good fit if you Have 6+ years of technical program management or business systems delivery experience, with a track record of owning a roadmap end to end Have worked in or close to a Salesforce-centric GTM or RevOps systems org and understand how lead, opportunity, partner, and quote objects connect Have managed delivery where multiple teams ship into one core system on a shared release process Have partnered with audit, controls, or compliance functions on revenue-impacting systems work Can build trust with business systems analysts, developers, sales operations, and finance, and translate between them Are comfortable driving outcomes across teams that don't report to you Are genuinely curious about how AI changes GTM operations and willing to experiment Strong candidates may also have Experience with one or more of: lead routing and scoring platforms, marketplace and co-sell tooling, CPQ, partner relationship management Background in RevOps, sales systems product management, or business systems analysis Experience standing up release management or CI/CD for a Salesforce org Familiarity with SOX ITGC or revenue controls Deadline to Apply: None. Applications are reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $290,000 — $365,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic is looking for a Partner Enablement leader to own how we enable our cloud partner ecosystem. Claude reaches a significant share of enterprise customers through AWS, Google Cloud, and Microsoft Azure, and the sellers, solution architects, and delivery teams inside those organizations are often the first people a customer talks to about deploying frontier AI. This role makes sure they are ready. You will translate Anthropic's product and go-to-market strategy into repeatable programs that help cloud partner field teams find, qualify, and win Claude opportunities, and then deliver them well. That means building the enablement infrastructure end to end: onboarding, launch readiness, sales and technical training, certification pathways, co-sell playbooks, and the metrics that tell us whether any of it is working. The job runs in both directions, and internal enablement is a sizable portion of it. Just as important as readying partner field teams is making sure Anthropic's own GTM organization knows how to work with the hyperscalers: which partnerships we have and what each one actually covers, how co-sell and marketplace mechanics differ across the three providers, when to pull a partner into a deal, and the offering nuances that determine what we can and cannot do through each channel. This is a build role as much as a run role. Cloud partner enablement at Anthropic is early, so you will be designing the operating model at the same time as you are shipping against a fast launch cadence. You will work closely with Partnerships, Applied AI, Product Marketing, Sales, and each hyperscaler's own partner and enablement organizations. Responsibilities You will own the cloud partner enablement strategy across AWS, Google Cloud, and Microsoft Azure, defining what "ready" means for each partner motion and building the programs that get partner field teams there. That starts with the co-sell motion: you will build the playbooks that let partner sellers carry Claude into enterprise deals alongside our own team, and you will make sure those assets map to how each hyperscaler's marketplace and co-sell mechanics actually work. You will design and run scalable enablement programs rather than one-off training. That includes onboarding paths for new cloud partner teams, role-based learning journeys for sellers and a repeatable launch readiness motion so partner teams are current on every new model and capability we ship. This work runs in both directions. You will also enable Anthropic's own GTM team, making sure sellers and partner-facing staff know which cloud partnerships we have and what each one covers, how co-sell and marketplace mechanics differ across the three providers, when to bring a partner into a deal, and the offering nuances that shape what we can do through each channel. Keeping the field current as those agreements and offerings change is a standing part of the job. You will build the content and the systems behind it, curating what lives in our partner portal and learning platforms, establishing review and refresh governance so nothing goes stale, and creating enablement assets that hold up in front of technical and commercial audiences alike. You will also partner directly with the enablement and partner development teams inside each cloud provider to land Anthropic content inside their channels, which is how this work reaches scale. Finally, you will instrument the program. You will define the metrics that connect enablement activity to partner-sourced pipeline, certification attainment, and deal velocity. You may be a good fit if you have Deep partner ecosystem knowledge, including a working understanding of how cloud co-sell motions operate in practice, from opportunity registration and marketplace transactions through to joint delivery Direct experience with one or more of AWS, Google Cloud, or Microsoft Azure, either from inside those organizations or from a partner or ISV working closely alongside them A proven track record building and maintaining enablement programs that scale, ideally from the ground up, with the certification frameworks, learning paths, and program operations to support them Experience enabling internal field teams, not just partners, on how to work with and through a partner ecosystem Strong go-to-market understanding and familiarity with enterprise sales cycles, enough to build content that sellers actually use and to speak credibly with field teams about pipeline and deal progression Excellent program management skills and the ability to run several concurrent workstreams against a fast launch cadence without losing track of quality Strong executive presence and the ability to influence stakeholders you do not manage, across both Anthropic and large partner organizations Exceptional communication skills, including the ability to translate complex technical concepts for mixed commercial and technical audiences Comfort operating in ambiguity, and a preference for building durable systems over shipping one-off deliverables Strong candidates may also have A background in enablement or product marketing Experience launching technical products or platform capabilities through a channel or partner ecosystem Familiarity with LMS and partner portal platforms, and with certification delivery at scale Hands-on familiarity with LLM and AI developer tooling, or a demonstrated ability to get technical quickly in a new domain The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $310,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Environments organization builds and maintains the infrastructure that improves Claude’s capabilities through reinforcement learning. That includes the frameworks researchers use to build environments and the infrastructure responsible for running them. The team's mission is to productionize research. You'll embed with research teams, get up to speed on how they work, and design the frameworks and APIs that let them move faster, building systems the team can understand, own, and maintain themselves. Scope also includes keeping production RL runs healthy, maintainable, monitored, and easy to triage. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and good intuition for how complex systems fail, especially silently. It's a bonus if you've built and operated a stateful distributed system, such as a workflow engine, actor framework, or durable-execution runtime, where correctness depends on getting shared state and recovery right. You should be comfortable diving into messy research code, finding the abstractions that matter, and improving them incrementally while researchers continue to build on your work. You should also be comfortable using AI tools to accelerate your own development, but have an impulse towards deep verification. Key responsibilities Design widely used APIs, frameworks, and abstractions that other engineers and researchers build on, making correct usage the default and ruling out entire classes of errors structurally Own the platform layers that sit beneath every environment, including the agent runtime Build the tooling that lets environment owners understand, debug, and maintain their environments in production without needing an infrastructure engineer in the loop Embed with research teams on a rotational basis, work directly in their codebases without slowing down the research they support, and transfer ownership when you rotate off Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that reduce the room for correctness issues Drive adoption of new frameworks across the organization, including deprecations and cutovers Help define the engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant code Strong taste in API and framework design, the ability to explain why an interface is right or wrong rather than just recognizing it, and a track record of other engineers or teams adopting and building on frameworks you have built Experience designing or operating stateful concurrent or distributed systems, and reasoning carefully about failure, retires, idempotency, and consistency A habit of verification: you measure before you conclude, and you build the checks that let a system show it's correct Experience working productively in large, evolving, or research-style codebases that you didn't originally write Strong written and verbal communication with collaborators of varied engineering backgrounds, and comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows, and familiarity with agentic systems or LLM training pipelines Experience building agent frameworks, orchestration engines, or multi-agent systems, including checkpoint and restore, replay, and coordination of long-running stateful processes Experience using AI coding tools on code where correctness matters, with good judgment about what to delegate and how to make the results verifiable Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing, dataset lifecycle management, or data lineage systems Experience designing serialization schemes, plugin systems, or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams and handing off systems for others to own, or defining code standards adopted across teams, or prior experience as a technical lead Representative projects These are examples of the challenges the team tackles: Design a base RL environment abstraction that can be subclassed to support the large majority of environments built across RL Redesign the model-tool interface for sandboxed agentic environments so that state is guaranteed to survive serialization, making it structurally impossible to write a tool that silently loses state Design the state-sharing and recovery model for multi-agent workloads, so that losing a sandbox partway through a task becomes a transparent resume rather than lost work Define the failure and retry model for a sandboxed execution platform, distinguishing infrastructure faults from genuine task outcomes so that each is handled correctly Build the tooling that lets an environment owner diagnose why their environment is unhealthy in a production run, and fix it themselves The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $605,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's Finance Systems team builds and owns the infrastructure that powers our financial operations and drives the initiatives that scale the Finance function as the company grows. As our financial operations grow in complexity, the team is moving beyond configuring off-the-shelf platforms and into building the production-grade financial applications that no vendor has built for us yet. You will own three things end to end: The architecture: design the treasury technology platform and data foundation, make the sequencing and build-vs-buy calls, and get the foundation right so we don't rebuild it in two years. The automation: turn Treasury's daily and monthly operating processes (cash positioning, cash flash reporting, forecasting, bank account management, payments) into tested, Claude-powered workflows that a lean team can run. The ecosystem: figure out how treasury technology plugs into the broader Finance data lake, the ERP, our banks, and vendor systems, so treasury is a well-governed node in the company's data architecture and ecosystems rather than an island on its own. You will be the bridge between the Treasury business owners and Finance Systems engineering, turning operational needs into a clear plan and driving it through to production. This is a foundational leadership role with significant ownership over architecture, vendor, and tooling decisions. You will shape how Anthropic sees and forecasts its cash, with room to grow the team and your scope as the function matures. In this role you will: Architect the platform Define the target-state architecture for treasury technology: the data foundation, the applications that sit on top of it, and how they connect Design the treasury data foundation (models, tables, pipelines, governance) as the single source of truth for banking, cash, payments, and investment data Lead the treasury management system build-vs-buy evaluation and own the resulting path - vendor selection and implementation, or the internal build Sequence the multi-year roadmap so foundational work lands before the capabilities that depend on it, with minimal throwaway work Automate key treasury processes Own the product roadmap for daily cash positioning, cash and liquidity forecasting, cash flash and leadership reporting, bank account management, treasury intake, and payment workflows Design and ship Claude-powered agents and dashboards that automate manual, error-prone treasury work, so a lean team can operate at scale Partner with Treasury operators to turn their processes into clear product specs, success criteria, and delivery plans, then drive them through to production Ensure everything we ship is auditable, controlled, and recoverable, with the rigor that SOX compliance demands as scope grows into controlled processes Define the ecosystem Align treasury data models and governance with the broader Finance data lake strategy so what we build now plugs in rather than gets rebuilt Map and own the integration surface across banks, bank connectivity providers, TMS, ERP, and internal finance systems Drive the technology agenda with our banking partners, TMS vendors, and connectivity providers tracking their technology roadmaps and partnering on emerging capabilities; partner internally with Accounting, FP&A, Internal Audit, and Data Engineering so treasury systems fit the company's control environment and architecture Run the function; set direction for and unblock one to two finance systems engineers; review technical designs You may be a good fit if you: Have 10+ years of experience in product management, technical program management, or systems leadership in finance, treasury, or fintech Have deep treasury domain knowledge, including cash positioning, liquidity forecasting, bank connectivity, cash pooling structures , or payment workflows Have owned the architecture and platform decisions for an internal finance or data platform across multiple systems and vendors Have a track record of shipping internal platforms or finance systems with an engineering team Have led complex system design and infrastructure programs, and are comfortable owning architecture and platform decisions across multiple systems and vendors Have led a system implementation (TMS, ERP module, or similar) or a material internal build from design through go-live Are a strong stakeholder manager across Treasury, Finance, Engineering, Internal Audit (Risk and Compliance)and external vendors Communicate clearly in writing and in the room, and can run a steering meeting or land a one-pager with executives Thrive in environments where the roadmap, the systems, and the team all need to be built at the same time Strong candidates may also have: Direct experience with treasury management systems such as Kyriba, Quantum, Trovata, or similar as owner, administrator, or implementer Experience integrating with banking APIs, payment rails, or bank connectivity providers Experience with cash pooling structures, intercompany funding, or multi-entity treasury operations Experience designing or overseeing finance data infrastructure (GCP/BigQuery or a comparable data warehouses, pipelines, reporting platforms) at a program level Experience at a high-growth technology company navigating rapid revenue expansion or system consolidation Built or product-managed AI/LLM-assisted workflows, agents, or Claude-powered automation for financial operations A CTP, CFA, or comparable treasury/finance credential is a nice to have The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Code RL at Anthropic drives reinforcement learning efforts behind Claude's coding capabilities, creating and scaling agentic coding environments. This is an engineering role with unusual latitude to set technical direction and standards. You'll be part of a team solving the engineering side of research efforts such as embedding with research teams, getting up to speed on their systems and needs, and designing the frameworks, APIs, and infrastructure that let researchers move faster, then rotating off, leaving behind well-oiled systems those teams can understand, own, and maintain themselves. Your remit also includes the ongoing health of production RL runs: maintainable, monitored, and straightforward to triage. The team's problem space spans the client side of sandboxed execution for agentic RL environments, large-scale data processing jobs, the lifecycle of production datasets, and the frameworks researchers build environments on. You won't own all of this yourself, you'll take on the slices where your depth matters most. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and hard-won intuition for how complex systems fail — especially silently. You should be comfortable diving into messy research code, finding the load-bearing abstractions, and improving them incrementally while researchers continue to build on top of your work. Key responsibilities Design widely-used APIs, frameworks, and abstractions that other engineers and researchers build on, with careful attention to interface legibility and principled defaults Embed with research teams on a rotational basis: understand their engineering needs, build systems and APIs that support their work, and transfer ownership so teams can maintain those systems after you rotate off Work directly in research codebases, improving reliability and structure without slowing down the research they support Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that shrink the surface area for bugs Contribute to the reliability of production RL systems, including monitoring, regression detection, and triage tooling Help define engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant Python code A track record of designing intuitive, safe APIs or frameworks that other engineers or teams adopted and built on Experience working productively in large, evolving, or research-style codebases that you didn't originally write Demonstrated ability to anticipate failure modes — especially silent ones — and prevent them structurally through system design, type safety, and testing Strong written and verbal communication skills, including the ability to explain system designs to collaborators with varied engineering backgrounds Comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows Familiarity with reinforcement learning concepts, agentic systems, or LLM training pipelines Experience building or operating large-scale distributed systems Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing or dataset lifecycle management Experience designing plugin systems or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams, including successfully handing off systems for others to own Experience defining code standards, lint rules, or static verification approaches adopted across multiple teams Prior experience as a technical lead, or setting engineering standards for a team Prior experience maintaining an open source project Representative projects These are examples of the challenges the team tackles; no one person will work on all of them: Design a base RL environment abstraction general enough to be subclassed across a wide range of environments Design a model-tool interface for sandboxed agentic environments that has explicit serialization semantics Partner with the platform teams that own the sandbox runtime to specify low-level features that improve the integrity of agentic coding tasks Design probes that catch sandbox regressions early Design the lifecycle and maintenance scheme for a production dataset Lead a research code refactor replacing loosely structured data containers with equivalents that carry stronger correctness guarantees, without breaking the experiments that depend on them Design lint rules and code-style requirements that favor statically verifiable patterns — including patterns less likely to be overlooked by an LLM reviewing or writing the code — to shrink the surface area for silent bugs Build the access layer that lets researchers discover and reuse data artifacts across teams The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $625,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. As Technical Recruiter, Infrastructure, you'll join the small team of recruiters who hire for that organization, owning full lifecycle recruiting for your searches and partnering with infrastructure leaders to turn ambiguous needs into clear search strategies. Key responsibilities Own full lifecycle recruiting for a portfolio of roles across the Infrastructure organization, from intake through offer and close Run structured intakes with infrastructure hiring managers, translating ambiguous needs into scoped requirements, calibrated bars, and search strategies Build and maintain pipelines of specialized infrastructure talent, with an emphasis on passive candidates Refine infrastructure interview loops, take-home assignments, and scorecards alongside hiring managers, your recruiting counterparts, and Recruiting Operations Develop deep domain knowledge aligned with the teams you support, so you can identify niche talent with the right specific domain fit Advise hiring managers with market data and candid calibration feedback, and influence decisions through credibility rather than volume Partner with Compensation, People Partners, and Mobility to structure equitable offers and guide candidates to close Handle sensitive role and candidate information with discretion, including for searches whose scope is confidential Minimum qualifications Deep full lifecycle recruiting experience, with substantial time supporting infrastructure, platform, or comparably technical engineering organizations Ability to hold a substantive technical conversation about infrastructure domains such as Kubernetes and container orchestration, cloud networking, cluster networking, and systems languages, and to evaluate technical qualifications rather than match keywords Proficiency with an applicant tracking system like Greenhouse and other modern sourcing tools Experience partnering directly with hiring managers on intake, bar calibration, and interview loop design Sound independent judgment on candidate quality, and the ability to independently partner with multiple hiring managers on complex searches A strong sense of ownership over your work, and the adaptability to adjust as priorities and hiring needs shift Genuine interest in Anthropic's mission and in the role a strong infrastructure function plays in achieving it Preferred qualifications Experience recruiting at a high-growth technology, AI, or machine learning company Working knowledge of the infrastructure and platform talent landscape, including where strong large-scale ML training and systems infrastructure talent tends to come from Experience hiring for hyperscale cluster infrastructure, research and platform infrastructure, privacy infrastructure, or sandboxing and isolation engineering Experience improving recruiting processes, market maps, or interview architecture where they were thin or absent Comfort using LLMs to accelerate sourcing, research, and market mapping The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 — $295,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. As we scale, our revenue is growing extremely quickly, our commercial agreements are getting more complex, and the related systems and controls need to keep pace. We are looking for a Head of Revenue Accounting, Deal Desk & Technical Accounting to own the accounting judgments behind that growth — the technical positions we take, the deals we approve, the disclosures we produce, the revenue systems that process it all, and the controls that make it dependable. You will act as the company's authority on complex revenue accounting questions. That includes developing our revenue recognition policies, leading enhancements to our revenue system, as well as designing, implementing, and operating our internal controls. You will set the bar for how much of this work Claude can do, so your team spends its time on key judgments rather than mechanics. Much of this role's impact comes through influence rather than authority. You'll shape deals before they're signed by getting to Sales and Legal early with a point of view on structures, and you'll shape our systems roadmap by advocating to engineering and systems partners for automation. This is a role for someone who can enable deal and business velocity while maintaining appropriate controllership. Key responsibilities Own technical accounting. Serve as the company's authority on complex revenue recognition matters — researching, concluding, and documenting positions in clear, well-reasoned memos, and explaining those conclusions to internal stakeholders and external auditors. Own the deal desk from accounting. Own our contract approval policy and its execution: define the accounting guardrails for non-standard terms, serve as the accounting approver in deal review, and partner with Sales and Legal to structure agreements that work commercially while maintaining appropriate controllership. Influence deal structures before they're signed. Build the credibility and relationships to shape how deals and programs are constructed rather than reacting to them — getting to Sales, Legal, and Finance early with a clear point of view, and making the accounting case in commercial terms that decision-makers can act on. Lead financial reporting and disclosure. Lead preparation of revenue related footnotes and technical disclosure positions, and build toward public-company reporting readiness. Lead the revenue system enhancements. Own the ongoing roadmap of our revenue system — requirements, design, testing, cutover, and post-launch optimization — partnering with Finance Systems. Influence the systems and automation roadmap. Advocate with engineering and system partners for the automation your team needs, translating accounting requirements into system priorities and building the working relationships that get them sequenced and shipped. Design and implement internal controls. Build controls over financial reporting for revenue and technical accounting processes, including documentation, testing, remediation, and audit support. Build scalable processes. Design well-documented processes that hold up as transaction volume and deal complexity multiply, replacing manual effort with automation. Apply Claude to the team's work. Utilize Claude to streamline processes, including accelerating research, drafting memos, reviewing contracts, and preparing reconciliations and disclosures. Enable growth while maintaining controllership. Partner across Sales, Finance, Legal, and systems teams to support new products, pricing models, and go-to-market motions, and advise leadership on accounting implications before decisions are made. Lead and grow the team. Set priorities, mentor the team, and raise the technical bar as the team scales. Minimum qualifications A track record of leading and developing a high-performing accounting team. Deep expertise in revenue recognition under ASC 606 for software, subscription, or consumption-based business models. Personal ownership of complex technical accounting research — writing position memos, defending those conclusions with external auditors, and preparing the resulting disclosures under US GAAP. Experience designing, implementing, and operating internal controls over financial reporting, including documentation and testing. Demonstrated ability to influence non-accounting stakeholders — shaping commercial deal and program structures with Sales and Legal, and shaping automation priorities with systems teams. Experience owning a revenue or billing platform (Zuora or comparable), either as implementation lead or as the accounting owner of its roadmap. CPA or an equivalent professional accounting qualification. Preferred qualifications Public company experience, or experience preparing a high-growth company for public reporting and SOX 404 compliance. Background at a national or Big Four firm. Experience with consumption-based, usage-based, or hybrid revenue models, particularly in AI, cloud, or infrastructure. Experience using large language models or AI tooling to automate accounting, contract review, or controls work. Experience standing up or overhauling a deal desk approval process. Hands-on Zuora implementation or operation experience. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $385,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for growth engineers to join our growth team. This key role will help drive user acquisition, engagement, retention, and monetization through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base! As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimize growth initiatives that scale our AI-powered tools and maximize their impact. Key responsibilities Develop and implement technical solutions to support user acquisition, activation, retention, and revenue growth Design and execute A/B tests and experiments to optimize user onboarding, feature adoption, subscription conversion, and overall product experience Collaborate with product and marketing teams to identify growth opportunities and translate them into technical requirements Minimum qualifications Experience working on user growth (acquisition, activation, retention, monetization) or have worked in a revenue focused organization like ads. Have experience full-stack development (web/React and backend), and experience with data analysis and experimentation frameworks Take a data-driven approach to problem-solving, with a keen eye for identifying patterns and opportunities in user behavior and metrics Are passionate about the potential of AI to reach and benefit a wide audience, and eager to tackle challenges in scaling AI products Thrive in a fast-paced, collaborative environment and enjoy working closely with cross-functional partners and teammates Preferred qualifications 5+ years of experience as a software engineer Have ideas for experiments to run to drive user growth or monetization Able to dive into data and identify opportunities Possess a vision for the future of AI product growth and a drive to make that vision a reality The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Recruiting Research Scientist to join our People Data Solutions team. You’ll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of recruiting funnels, interview effectiveness, candidate experience, and recruiting capacity. This role sits at the intersection of organizational science, behavioral research, and people strategy – developing novel frameworks and conducting systematic research that drives evidence-based people decisions across our growing organization. This role offers the opportunity to make a significant impact on both our recruiting practices and the broader field of people science at a leading AI safety company. Responsibilities Research design & scientific inquiry Design and execute systematic research studies to answer fundamental questions about recruiting funnel health, assessment quality, candidate experience, and quality of hire Generate and test hypotheses about sourcing strategies, interview design, and selection decisions using rigorous experimental and quasi-experimental methods Conduct mixed-method research to understand what are the drivers and blockers to recruiting operations. Navigate research ethics considerations when studying candidate data, ensuring responsible research practices Selection & assessment research Design and execute validation studies to assess the quality of interviews and other selection tools Utilize psychometric techniques to analyze and improve interviewer calibration and rating consistency Lead investigative research into innovative approaches for candidate assessment Metrics design and governance Design the metrics framework for recruiting org health — defining the canonical KPIs, dimensions, and definitions that leadership uses to understand funnel performance, capacity, and hiring quality Establish the governance and definitional rigor that keeps metrics consistent across tools and reporting surfaces Analytical solution building Architect analytical solutions that convert research insights into actionable products, empowering stakeholders to execute data-driven scenario and strategic planning Quantify the adoption and downstream impact of deployed tools, driving iterative improvements Visualization & communication Build compelling visualizations and dashboards that make complex research findings accessible to diverse audiences Present research findings to senior leadership with clear, actionable recommendations Minimum Qualifications: Hold an advanced degree (Master’s or PhD) in I/O Psychology, Organizational Behavior, Statistics, Data Science, Economics, Behavioral Science, or a related research field Have experience with selection research, assessment validation, psychometrics, or recruiting funnel analytics Are comfortable working in the People Analytics tech stack and collaborating with data engineers Are proficient in SQL and Python/R, with experience in statistical analysis and machine learning Have experience with data visualization and can tell compelling stories with research findings Possess excellent communication skills and can influence stakeholders at all levels Thrive in ambiguity and can balance rigor with pragmatism Have a track record of challenging assumptions with data and changing long-held practices Can navigate sensitive topics diplomatically while maintaining analytical rigor Demonstrate intellectual humility and comfort with iterative discovery Use data to improve how organizations find, assess, and hire talent Preferred Qualifications: 5 + years of experience in research, people analytics, or related quantitative fields with demonstrated research methodology expertise Background in recruiting analytics specifically (not just general analytics) Experience running interview or assessment validation studies Experience building self-service analytics tools or dashboards Previous experience in high-growth technology companies or AI/ML organizations Familiarity with network analysis, machine learning, or advanced statistical methods Experience with BigQuery and modern data stack tools Experience with Greenhouse, Gem, ModernLoop, or similar recruiting tools The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $285,000 — $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.