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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 As a Data Engineer on the Safeguards team, you will build the data foundations that keep our AI systems safe. The Safeguards team works to monitor models, prevent misuse, and ensure user well-being — and doing that well requires robust, reliable data infrastructure. In this role, you will design and build the pipelines, warehousing solutions, and analytical tooling that power our safety and trust efforts at scale. You'll work closely with engineers, data scientists, and policy teams to ensure the Safeguards organization has the data it needs to detect abuse patterns, measure the effectiveness of safety interventions, and make informed decisions about model behavior and enforcement. This is a high-impact role where your work directly supports Anthropic's mission to develop AI that is safe and beneficial. Key responsibilities Design, build, and maintain scalable data pipelines that support safety monitoring, abuse detection, and enforcement workflows Develop and optimize data models and warehousing solutions to enable efficient analysis of large-scale usage and safety data Build and maintain dashboards and reporting infrastructure that give Safeguards teams visibility into model behavior, misuse patterns, and enforcement outcomes Collaborate with engineers to integrate data from multiple sources — including model outputs, user reports, and automated classifiers — into a unified analytical layer Implement data quality frameworks, monitoring, and alerting to ensure the reliability of safety-critical data Partner with research teams to surface data insights that inform model improvements and safety interventions Develop self-service data tooling that enables stakeholders to explore safety data and generate reports independently Contribute to data governance practices, including access controls, retention policies, and privacy-compliant data handling Minimum qualifications Proficiency in SQL and Python, with hands-on experience building and maintaining ETL/ELT pipelines Experience with cloud data platforms such as BigQuery, Redshift, Snowflake, or similar Experience with modern data stack tools such as dbt, Airflow, Spark, or similar orchestration and transformation frameworks Experience building dashboards and data visualizations using tools such as Looker, Tableau, or Metabase Ability to communicate clearly and translate complex data concepts for both technical and non-technical audiences Preferred qualifications 8+ years of experience in data engineering, analytics engineering, or a related role Comfort contributing across the stack and picking up work outside your immediate scope when the situation calls for it Background in trust and safety, integrity, fraud, or abuse detection data systems Experience with large-scale event streaming systems such as Kafka, Pub/Sub, or Kinesis Experience building data infrastructure that supports ML model monitoring or evaluation Familiarity with data privacy and compliance frameworks such as GDPR, CCPA, or similar Background in statistical analysis or experience working closely with data scientists A genuine interest in the societal implications of AI and in making AI systems safer 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 hiring an Engineering Manager to lead a team of engineers building AI-powered cybersecurity products. The work spans research, product, and go-to-market. Your team will prototype and ship products that use frontier models to defend code and infrastructure. You will set technical direction, partner with research to turn new model capabilities into products, and stay close to customers so the team builds the right things, not just builds things well. This is a builder's role. The team is small, the pace is high, and you should expect to be in the code, in customer calls, and in research reviews the same week. You also need to scale the team without losing the prototyping energy that got the product here. Responsibilities Lead and grow the team: hiring, performance, and the culture that keeps strong engineers doing their best work Stay close to customers, design partners, and the security community; turn what you learn into products and unblock the team on the ones that matter Own architectural decisions across the full stack, from agentic systems and model orchestration to product surfaces, integrations, and data infrastructure Coordinate with GTM, partnerships, and other product areas Grow the next layer of leadership on the team You may be a good fit if you Have 8+ years of software engineering experience and 4+ years managing engineers, with ownership of a team's hiring, performance, and technical direction Have shipped cybersecurity products in production (SIEM, EDR, vulnerability management, application security, threat detection, incident response, or security automation) Have taken a team from prototype through first paying customers to scaled deployment Are technical and hands-on: comfortable in design reviews and in the team's code Have strong product instincts and a record of helping teams decide what to build, not just how Communicate clearly across functions and keep research, product, GTM, and executive partners aligned through ambiguity Treat direct customer contact as a primary input to your roadmap Care deeply about Anthropic's mission and about developing AI responsibly and safely Strong candidates may also have experience with Hands-on security expertise: application security, vulnerability research, reverse engineering, incident response, penetration testing, or detection engineering Building products on LLMs, including agentic systems, evals, and prompt and model iteration loops Strict data-handling environments (BYOC, CMEK, regulated industries, governments) Both startup and enterprise-scale company experience Working closely with research to translate capability into shipped product Ecosystem partnerships and MCP, CI/CD, or source-control integrations 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 — $485,000 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 RL teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Fable 5 and Opus 4.8. Our work spans several key areas: Developing systems that enable models to use computers effectively Advancing code generation through reinforcement learning Pioneering fundamental RL research for large language models Building scalable RL infrastructure and training methodologies Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at. You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will: Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization. Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards. Conduct experiments and shape our roadmap. Deliver your work into research and production training runs. Collaborate with other researchers and engineers across and outside Anthropic. You may be a good fit if you: Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs. Are fluent with industry EDA tools and processes. Have taped out chips and have experience going from spec to silicon. Know how to balance research exploration with engineering implementation. Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have: Experience with reinforcement learning, evaluations or environments. Built tooling or automation around chip design flows. Worked on ML accelerators or high-performance compute hardware. Familiarity with high-level synthesis or architecture simulators. 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: $500,000 — $850,000 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 As one of our first Data Scientists dedicated to policy work, you will play a key role in ensuring Anthropic's work is understood by policymakers around the world. You'll sit at the intersection of data science and public affairs, transforming internal product usage and survey data into clear, accurate, and consistent evidence the Policy team can use to inform its positions, demonstrate Anthropic’s relevance to policymakers, and measure the impact of its work. Your analyses will directly inform how legislators, regulators, and the public understand Anthropic's footprint and contribution. This is a highly cross-functional role that is foundational to Anthropic's mission of bringing powerful AI to the world in a way that benefits humanity. Key responsibilities Partner with product and business teams across the company to produce supporting analyses and data collateral for specific policy position papers and partnership conversations Determine which metrics faithfully represent our company to legislators, regulators, and the public Own the dashboards and pipelines that keep externally-shared numbers consistent, so the Policy team can move quickly without creating discrepancies Use AI tools to aggregate news, policy developments, and other public data sources to track trends and provide a clear picture of the evolving regulatory landscape Develop measurement frameworks for policy communications, paid media, and public-affairs campaigns Design and implement policy analyses to support internal position development or measure the impact of policy implementation for external audiences Minimum qualifications Proficiency in Python, SQL, and data analysis tools, with experience working with external and public data sources Experience producing analysis that reaches external audiences such as policy, communications, investor relations, public affairs, or published research Applied causal inference using quasi-experimental designs (e.g., difference-in-differences, regression discontinuity, synthetic control, instrumental variables, or matching) to measure policy or program impact from observational data Demonstrated ability to translate complex analyses into clear, actionable recommendations for audiences with differing levels of technical fluency Preferred qualifications 6+ years of hands-on data science experience Direct experience supporting a policy, government affairs, or regulatory team with data and analysis Familiarity with investor-relations or financial-disclosure data standards and the consistency requirements they entail Comfort operating in ambiguous, fast-moving environments where creating clarity and driving progress is part of the role A genuine interest in Anthropic's mission of building safe and beneficial AI Deadline to apply: None. Applications will be accepted 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: $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.
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 At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Claude Design is the newest product from Anthropic Labs, the internal accelerator behind Claude Code and MCP. It lets anyone collaborate with Claude to create polished visual work: interactive prototypes, product mockups, slides, one-pagers, and marketing collateral. Start from a prompt, an image, or your own codebase, and Claude builds a first version that you refine through conversation, inline comments, direct edits, and live adjustment controls, then hand off to Claude Code to build for real. We launched in research preview in April 2026, and the product is new enough that the engineers who join now will define what it becomes. We're looking for Software Engineers to help build and shape Claude Design. This is a craft-heavy, frontend-leaning role: you'll create the canvas, real-time editing, design-system inference, and AI-driven generation experiences that make AI-generated design feel like a tool people reach for first– not a demo. You'll work at the intersection of cutting-edge research and real-world application, rapidly building and testing new experiences, partnering directly with researchers and users, and helping to generate the crucial insights that shape where the product goes next. Responsibilities Build and ship Claude Design's core surfaces (the design canvas, real-time editing, inline comments, and the live adjustment controls Claude generates), shipping early and often to maximize learning Collaborate closely with research teams to turn frontier vision and generation capabilities into intuitive, high-craft design experiences Work directly with designers, internal test users, and external partners to gather feedback, iterate quickly, and validate (or invalidate) product concepts Set technical direction for the hardest frontend problems: editor and canvas architecture, real-time collaboration, design-system inference, rich import/export, and performance as the product scales Design and run experiments to test product hypotheses, from prototype tests with users to evaluations of generation quality, balancing creative exploration with rigorous measurement Own the quality bar for how the product looks and feels, treating latency, responsiveness, and reliability as first-class concerns rather than afterthoughts, and advocate for user experience and design considerations early in the process Strengthen the handoff to Claude Code so designs translate cleanly into production, and feed insights back to research about model effectiveness and where capabilities can improve Operate as a technical leader on a small team: shape the roadmap alongside design and product, make pragmatic architecture decisions, and mentor engineers as the team grows You may be a good fit if you Have 8+ years of experience building full-stack applications with deep frontend strength, and a track record of zero-to-one work in startup or startup-like environments Have set technical direction for a team or workstream and mentored other engineers, while staying hands-on in the code Have strong design sensibility and a high bar for craft; you sweat interaction details, motion, and polish Have strong technical skills across modern web stacks (React, TypeScript, Node.js, Python, Go, etc.), including complex client-side state, performance, APIs, databases, and cloud technologies Are comfortable working in a fast-moving environment where priorities shift and shipping quickly matters Are deeply user-centric: you enjoy validating ideas with actual users before over-investing and you talk about problems before solutions Hold strong opinions loosely: you advocate forcefully for ideas but change your mind based on evidence Are a generalist who can move comfortably between frontend, backend, and product problems as the work demands Work independently with good judgment about what matters, without needing constant direction Communicate effectively and translate complex AI capabilities into intuitive experiences Care about the societal impacts and ethics of your work Strong candidates may also have Extensive experience working with or building visual collaboration & creative tools (e.g., Figma, Canva, Adobe Creative Cloud, etc), and have strong opinions on how they could become more magical experiences Hands-on experience with UI/UX for AI-powered applications, and fluency collaborating closely with designers Background conducting user research, interviews, and usability testing Deep frontend expertise in canvas rendering, complex editor UIs, design-system tooling, or graphics work (WebGL/shaders, 3D, animation) Experience with real-time, collaborative applications (multiplayer editing, WebSockets) or complex, high-performance frontend interactions Candidates need not have 100% of the skills listed above Formal certifications or education credentials Direct machine learning or AI research experience Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. 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 — $485,000 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 hiring Support Engineers to serve as the named, dedicated Product Support point of contact for Anthropic's most strategic enterprise customers. As a Support Engineer, you'll be providing high-touch, deeply contextual support to a defined book of accounts — embedded in your customers' shared channels, known by name to their stakeholders, and partnering closely with Sales, Customer Success, and Applied AI as the technical support voice on the account team. You'll bring deep knowledge of how each of your customers is built on Claude to every interaction, so you can investigate, diagnose, and resolve their most complex technical needs with nuance and speed — and ensure the right internal teams are engaged when needed. Responsibilities Serve as the named technical support contact for a defined book of strategic enterprise accounts, embedded in customer channels and joining recurring account cadences as the support voice Own your customers' technical support needs end to end — investigate, diagnose, and resolve complex issues directly, and partner with internal Engineering and Product teams to drive resolution when needed Build deep, durable context on each customer's architecture, integrations, and use cases so you can respond with nuance rather than from a script Partner closely with the Customer Success Manager, Account Executive, and Applied AI team on each account as part of a single, coordinated account team Capture technical feedback and product friction from your accounts and route it to Product with the impact data and detail needed to prioritize it correctly Manage high-urgency issues for your accounts with extreme ownership, and coordinate cleanly with the broader Product Support team for continuous coverage Help build the foundations of the Support Engineer function — runbooks, escalation paths, tooling, and the metrics we'll use to measure its value Become an expert in all Anthropic products across the API, Claude for Enterprise, and Claude Code You may be a good fit if you Have 5+ years in technical product support, with meaningful time in an escalated, priority, or named-account support team for enterprise customers Have been the person an enterprise customer knows by name and reaches for first when they need technical help Are deeply fluent with APIs and technical SaaS products, and can read technical documentation, error logs, and request traces with ease Have hands-on experience troubleshooting SSO, SAML, OAuth, and enterprise authentication flows Are persistent and curious — you delight in the hunt of tracking down a bug, and are energized by fixing it for every similar user going forward Possess strong user empathy and crisp, kind written communication; you can translate between a frustrated customer engineer and an internal platform team without losing either Are comfortable operating in ambiguity, making informed decisions in never-before-seen situations, and knowing when to pull the escalation cord Enjoy building trust and collaborating closely with go-to-market partners (Sales, CS, Applied AI) without owning the commercial relationship yourself Have contributed to the foundations of a support team before — the essential, often unglamorous work of writing the first runbook Are excited about Anthropic's products and the opportunity to shape how the world's largest companies get support for them Strong candidates may also have SQL proficiency for querying logs and usage data to investigate issues Comfort with command line interfaces and basic scripting (Bash, Python, JavaScript) Understanding of LLM capabilities, prompt engineering patterns, and current limitations Familiarity with enterprise networking concepts, cloud infrastructure (AWS, GCP), and IT environments Experience working inside a customer's shared Slack or similar embedded-support model Background as a Technical Account Manager, Support Engineer, or Designated/Premier Support contact at a developer-platform or infrastructure company 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: $210,000 — $250,000 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 inference fleet serves Claude to millions of users across our own products and the world's largest cloud platforms. The stack that makes this possible is deep and tightly coupled: accelerator kernels, model servers, distributed routing, autoscaling, capacity management. Every layer affects the others, often in ways that are hard to see in isolation. The Inference System Dynamics team is responsible for understanding that whole system and holding it to a high bar across four dimensions: throughput, latency, reliability, and correctness . We measure how the fleet performs against its theoretical performance frontier, run cross-layer investigations to explain the gaps, and own the correctness checks that make sure Claude's outputs are right, not just fast, across hardware platforms and serving configurations. We don't own the individual components. We instrument and model them, find the highest-leverage opportunities across them, and partner with the owning teams to land the wins. You'll work across all four areas. One week that might mean tracing a tail-latency regression from request timing down through routing and batching into a kernel overhead; the next it might mean tightening a correctness eval so it catches an output regression introduced by a quantization change. We're looking for performance engineers who treat correctness as part of performance. Key Responsibilities Run cross-layer performance investigations across throughput, latency, and reliability, sizing the gap between actual fleet performance and theoretical rooflines, identifying root causes, and quantifying the value of closing them Own and improve the correctness evaluation pipeline that validates model output quality across hardware platforms, numerics, and serving configurations, and lead the investigation when it catches a regression Build the observability, dashboards, and modeling tools that make throughput, latency, cost, reliability, correctness, and their interactions legible across the stack Partner with kernel, serving, routing, autoscaling, and capacity teams to prioritize and land the highest-impact optimizations your analysis surfaces Ruthlessly stack-rank a large surface area of opportunities by impact and effort, and say no to the ones that don't make the cut Minimum Qualifications Hands-on performance engineering experience: profiling, roofline analysis, latency/throughput optimization, and root-cause investigation in complex production systems Proficiency in Python, with the ability to read, instrument, and contribute to large production codebases you didn’t write Solid data analysis skills (e.g. SQL, pandas, or similar) sufficient to turn raw telemetry into clear findings Ability to communicate quantitative results clearly in writing to influence priorities on teams you don't manage Genuine interest in correctness as an engineering discipline: numerics, evaluation design, regression detection Preferred Qualifications Experience with ML systems, especially training or inference infrastructure or general LLM serving stacks. Direct large-scale inference experience is a strong plus Familiarity with GPU/TPU/accelerator performance concepts (memory bandwidth, kernel overheads, quantization, collective communication). Reasoning about these matters more than having written kernels yourself Experience with reliability engineering for high-throughput services: autoscaling, load balancing, request routing, tail latency Experience with model evaluation or numerical regression-detection pipelines Experience building observability or telemetry for distributed systems Comfortable having impact through influence and evidence rather than direct ownership Representative Projects Trace a 350ms latency gap on a new accelerator platform from end-to-end request timing down to a server scheduling overhead, quantify the win, and land the fix directly or with the owning team Redesign the correctness eval gate: determine which signals reliably catch real model-output regressions versus noise, and make it the trusted release criterion across hardware backends Build a FLOPs funnel that breaks down where compute actually goes across the fleet, exposing the gap between achieved throughput and kernel rooflines Root-cause a numerical divergence between two hardware platforms to a specific kernel change, and define the acceptance threshold going forward Model the latency–cost impact of changing batch-sizing and utilization targets, and turn the result into the signal the autoscaler uses in production Deadline to apply: None. Applications will be 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: $350,000 — $850,000 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 Research Tools team builds systems that support our large-scale, distributed finetuning runs and improve the productivity of researchers. As a manager, you’ll support a team of machine learning and distributed systems experts to make these systems and tools highly efficient, support fast iteration on model development and research, and evolve the infrastructure continuously to incorporate new research advances. Our Research Tooling sits at the intersection of almost every technical group at Anthropic. You’ll work with research teams to incorporate their innovations into our production finetuning pipeline, product teams to help us iterate quickly on customer-oriented model improvements, and infrastructure teams to make sure our training runs and data pipelines are as efficient as possible. 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 society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business, and product. Responsibilities: Prioritize the team’s work in collaboration with the technical lead, research teams, and product teams to support fast iteration on research projects and training runs. Design processes (e.g., postmortem review, incident response, on-call rotations) that help the team operate effectively. Coach and support your reports to understand and pursue their professional growth. Run the team’s recruiting efforts efficiently, ensuring we can grow as quickly as we need through a period of rapid growth. You may be a good fit if you: Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well. Are an experienced manager (at least 2 years) and actively enjoy people management. Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level) to be effective. Strong candidates may also have: Experience working with research teams, especially as part of a “research to production” pipeline Strong people management experience: Coaching, performance evaluation, mentorship, career development Strong project management skills: Prioritization, communicating across team/org boundaries Experience recruiting for your team: Predicting staffing needs, designing interview loops, evaluating candidates, and closing them Deadline to apply: None. Applications will be 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: $405,000 — $850,000 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 As a Technical Program Manager for Product, you'll drive the programs that bring Anthropic’s AI capabilities to the world. You’ll work closely with research teams to understand new model capabilities, then orchestrate across engineering, product, infrastructure, and go-to-market teams to ensure we launch reliably and at pace. This role is essential in orchestrating the cross-functional effort required to launch successfully as Anthropic continues to scale. This role offers unique challenges in coordinating high-stakes technical programs while maintaining the quality and reliability our customers expect. This position requires deep technical fluency, the ability to earn trust with researchers and engineers, and a talent for driving alignment across teams with different priorities and working styles. Responsibilities Lead end-to-end program management for model and product launches, coordinating between research, engineering, product, infrastructure, and partnership teams Drive cross-functional alignment and decision-making across workstreams, ensuring teams are unblocked and launches stay on track Partner closely with Research PMs and engineering leads to sequence work, manage dependencies, and navigate technical tradeoffs Track and communicate program status, risks, and dependencies to leadership and stakeholders Build strong relationships with technical stakeholders, earning trust through deep engagement with the details Coordinate with research teams to understand upcoming model capabilities and prepare launch plans accordingly Navigate tradeoffs between speed, quality, and scope, helping teams make informed decisions under pressure Develop and improve launch processes, playbooks, and operational frameworks that scale with our growing complexity Create and maintain documentation of launch processes, decision logs, and cross-functional dependencies You may be a good fit if you Have several years of experience in technical program management, with a track record of successfully delivering complex, cross-functional programs Possess deep technical knowledge that allows you to engage meaningfully with ML researchers and engineers Have experience managing programs with significant external dependencies and multiple stakeholder groups Excel at translating between technical teams and stakeholders, making complex tradeoffs understandable Can thrive in ambiguous situations, bringing structure to complex technical challenges Have strong organizational skills and can manage multiple parallel workstreams effectively Are comfortable operating at a fast pace where priorities shift and new challenges emerge quickly Have excellent written and verbal communication skills, with the ability to influence without authority Build trust quickly and maintain strong relationships even under pressure Are passionate about Anthropic's mission and interested in the challenges of bringing frontier AI capabilities to users safely 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: $365,000 — $435,000 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 As an early member of our Safeguards Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by building and scaling a data driven culture from the ground up. In this unique company, technology, and moment in history, your work will be critical to informing our product and commercial strategy as we deploy safe, frontier AI at scale to the world. You will work closely with product, engineering, policy & enforcement to define and measure key company success metrics, analyze user behavior to identify new enforcement opportunities and build a culture of developing and testing hypotheses through experimentation. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to building robust and scalable systems and processes as our company goes through a phase of rapid growth. Key responsibilities Deep dive into user behavior data to provide insights on safety concerns Define core metrics that measure the team's success. Set goals, build forecasts, monitor performance, and develop actionable reporting Identify and size opportunities to improve the product, influencing product roadmap through your insights and recommendations Develop hypotheses on product changes, design controlled experiments, analyze the results, and make recommendations based on impact to key metrics Build a data driven culture from the ground up by establishing foundational data best practices and making data more accessible across the company Minimum qualifications Expertise in Python, SQL, and data visualization tools. A bias for action and urgency, not letting perfect be the enemy of the effective. A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress. A deep curiosity and energy for pulling the thread on hard questions. Experience in turning open questions and data into concise and insightful analysis. Highly effective written communication and presentation skills. A passion for the company's mission of building helpful, honest, and harmless AI. Preferred qualifications 8+ years of experience in data science or analytics roles, preferably in an infrastructure or operations context. 3+ years of experience deeply embedding in Product teams. Experience working on safety, anti-abuse, integrity shaped problems. Deadline to apply: None. Applications will be 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: $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.
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 seeking a Director, Revenue Controls to be the Accounting owner of the control environment over our order-to-cash cycle. Revenue at Anthropic includes subscription and consumption, self-serve and enterprise motions, 1P and 3P channels, and a metering pipeline that feeds billing and revenue recognition. You will report to the Revenue Controller and partner closely with Accounting, Systems, and Internal Audit stakeholders as we build toward SOX 404 compliance. You will be expected to understand the systems and processes impacting revenue and own/influence the design and implementation of sufficient internal controls, including obtaining relevant SOC reports from service-providers, as well as be the face of the revenue team with external auditors. This is not a greenfield solo build. You will be joining an established Revenue team with functional leads across order management, collections, and revenue accounting, alongside dedicated engineering and systems partners. Your job is to bring senior judgment, sequencing, and control discipline to a group that is already moving fast - leading through a team and across functions rather than doing it all yourself. Key responsibilities Serve as the accountable first-line control owner for order-to-cash and revenue business process controls, including control design, documentation, execution, and related evidence Maintain the order-to-cash process narratives, SOPs, and process maps as the institutional standard, and keep them accurate through system and business changes Partner with functional leads across Billing, AR & Collections, Deal Desk, and Revenue Accounting to keep process definitions current and consistently executed Design and influence the implementation of controls over usage capture and rating, contract-to-billing accuracy, invoice completeness, cash application, credit and adjustment approvals Own the identification and control treatment of key reports and Information Produced by the Entity (IPE) within the revenue cycle, including completeness and accuracy validation for reports used in controls and in the close Partner with Revenue Technology and Internal Audit on IT-dependent and automated controls in the revenue stack - including interface and reconciliation controls, configuration change governance. Embed control requirements into new system implementations and process changes at design time Partner with third-party service providers to understand their processes, identify relevant risks, and secure commitment for relevant SOC 1 reports Work with the Internal Audit on scoping, walkthroughs, testing, and deficiency evaluation for revenue processes; own remediation design and drive it to closure Get involved early with Product, Sales, Partnerships, and Legal on new offerings, pricing constructs, and go-to-market motions to assess order-to-cash and control implications before launch Diagnose recurring breakdowns, trace them to root cause, and drive fixes to closure with the accountable owner Train and enable process owners and control performers on control execution, evidence retention, and what audit-ready means Support external auditors as the process owner for order-to-cash walkthroughs and testing Serve as the Revenue organization's primary business partner to the Revenue Systems teams - translating accounting and control requirements into system requirements, and system constraints into workable process design Represent Revenue in the design, configuration, testing, and cutover of revenue and billing systems, including the ERP environment, revenue subledger, metering and billing platforms, CPQ, tax, and payments Own the internal control go-live readiness criteria for revenue system changes, including data validation and reconciliation between upstream metering, billing, and the general ledger Minimum qualifications Experience supporting SOX 404 readiness at a pre-IPO company, or operating within a public company reporting environment Bachelor's degree in accounting, finance, or a related field (or equivalent experience) Deep, hands-on SOX experience over revenue and order-to-cash processes — you have designed controls, not just described them, and you understand control objectives, IPE, and sufficiency of audit evidence. Experience as the business-side owner or lead partner on revenue system implementations, migrations, or major configuration changes, including requirements definition, UAT, and reconciliation of data across the revenue stack. Working knowledge of ASC 606 and the practical mechanics of how contracts, usage, and billing translate into recognized revenue. Experience in consumption and subscription revenue models, and systems processing large transaction volumes and large datasets A track record of influencing across stakeholders without direct authority. Precision communication — you can write a process narrative for an auditor, a steering committee update for leadership, and a root-cause summary for an operating team. Comfort operating in ambiguity, with the judgment to distinguish what needs to be controlled now from what can wait. Preferred qualifications 15+ years of progressive experience in internal controls, revenue operations, revenue accounting, and finance transformation. CPA, CIA, or comparable certification Big 4 audit, risk advisory, or finance transformation background Hands-on experience with mainstream ERPs and revenue engines — and with metering, billing, tax, and payments platforms Familiarity with third-party marketplace billing dynamics (AWS, GCP, Azure) and channel or reseller arrangements Experience with SOX or GRC tooling SQL and comfort working directly with revenue data to validate what the systems are telling you Lean, Six Sigma, or other formal process improvement training Strong interest in applying AI and automation to revenue operations, control monitoring, and evidence collection 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 Anthropic's research organization works across the full model development lifecycle, from pre-training and post-training to alignment, interpretability, and safety, each operating at the frontier of AI development. As a Technical Program Manager for Research, you'll define and build the programs that research teams need most. You'll move across research areas like compute, evals, RL environments, and emerging research initiatives, going deep enough in each to understand how researchers work and what they need. You'll identify where the biggest opportunities for impact lie, find the highest-leverage gaps, and build the programs, processes, and tooling that allow researchers to focus on research. This is a 0-to-1 role: you'll explore new domains as priorities shift, determine what each one needs, and create lasting impact where none existed before. Note: This role may require responding to incidents on short-notice, including on weekends. Responsibilities Embed deeply within a research domain to understand the technical landscape, build trust with researchers and technical leaders, and identify the highest-leverage problems to solve, knowing the surface area will shift over time as research priorities evolve Move fluidly across research areas like compute, evals, RL environments, and emerging research initiatives, picking up new domains quickly and getting to depth fast Drive end-to-end execution of complex, ambiguous research initiatives spanning multiple teams, often without established playbooks or precedent Establish processes and frameworks that bring structure to unstructured research environments without slowing researchers down Lead efforts like large-scale compute resource planning, including allocation, efficiency, and prioritization across research and production workstreams Drive eval readiness for model launches by standardizing results, shaping eval plans early, improving tooling, and ensuring honest, transparent reporting across research, product, and marketing Own execution and operational health of RL environments across major training runs, coordinating cross-team trade-offs and feeding insights back into roadmap planning Equip research leadership to make decisions quickly by going deep on technical tradeoffs and presenting clear, actionable recommendations Act as the connective tissue between research, engineering, and product teams to reduce chaos and accelerate execution You May Be a Good Fit If You Have a background in ML research or engineering with several years of experience building technical programs from scratch, ideally with hands-on exposure to training, evaluation, or large-scale distributed systems Are a fast learner who can ramp on unfamiliar technical domains quickly and contribute meaningfully to discussions with researchers Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in fast-moving research environments Have a track record of operational ownership of complex technical systems, including monitoring, incident response, and performance optimization Can reason about technical tradeoffs at depth across model architecture, training infrastructure, evals, or compute efficiency, and translate them into clear decisions for leadership Have excellent stakeholder management skill and the ability to influence senior technical staff through competence and consistent delivery Are comfortable with high-stakes environments where decisions impact compute spend, model training timelines, and launch outcomes Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems Are excited to redefine what technical program management looks like at the frontier of AI research 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: $365,000 — $435,000 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.