Anthropic has 145 active AI-related job listings. The majority of these roles are focused on agents, comprising 28% of the total. Engineering is the most frequent function, with 74 listings, followed by Research with 51. The company is primarily hiring in the United States, with 118 positions, and the United Kingdom, with 22. Frequent tech tags include model_serving, evals, and agent_orchestration, suggesting a focus on deployment and evaluation of AI systems. In the last 30 days, Anthropic posted 16 new AI roles, a 47% decrease compared to the previous 30-day period.
Currently tracking 124 active AI roles, with 106 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $46k–$850k (avg $405k).
Anthropic currently has 132 active AI-related roles in our index. The most common open titles are: Applied AI Architect, Industries (2), Regional Research Economist, Economic Research (2), Research Engineer, Machine Learning (RL Velocity) (2), Research Engineer, Production Model Post-Training (2), Staff Software Engineer, AI Reliability Engineering (2). Most positions are in Engineering and Research.
Anthropic's active AI hiring is concentrated in: agents (28%), serving infrastructure (17%), post-training (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Anthropic is hiring AI talent in: United States (106 roles), United Kingdom (20 roles), Canada (6 roles), Ireland (5 roles).
Job postings at Anthropic most frequently reference: model serving, evals, llm observability, agent orchestration, inference infra.
In the past 30 days, Anthropic has posted 29 new AI-related roles. That is a +61% change versus the prior 30 days (18 → 29).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer, Safeguards Research Machine Learning Engineer focused on safeguards research, bridging research and engineering. This role involves developing end-to-end pipelines and ML systems for safety research, including training/fine-tuning models, building scalable infrastructure for evaluation, implementing efficient training pipelines, and creating automated systems to understand and mitigate AI risks. The role requires strong ML fundamentals, engineering practices, and experience with Python, ML frameworks, and LLMs. | Post-trainServe | 9 |
| Research Engineer, Reward Models Research Engineer focused on developing and implementing novel reward modeling architectures and techniques to align AI systems with human values and advance AI capabilities. The role involves optimizing training and data pipelines, collaborating on integrating advances into production systems, and communicating research progress. |
| Post-train |
| 9 |
| Research Engineer, Production Model Post-Training Research Engineer focused on post-training of large language models, including techniques like Constitutional AI and RLHF, to enhance model capabilities, alignment, and safety for production Claude models. Involves implementing, scaling, and optimizing these processes, conducting research for improvements, and developing evaluation tools. | Post-train | 9 |
| Machine Learning Systems Engineer - Infrastructure & Runtime, Horizons Machine Learning Systems Engineer focused on building and maintaining foundational infrastructure for AI research, specifically for reinforcement learning, agentic AI, and model evaluation. The role involves designing data pipelines, creating secure execution environments, optimizing distributed computing infrastructure, and translating research requirements into scalable systems. | DataAgent | 9 |
| Machine Learning Systems Engineer - Data & Evaluation, Horizons Machine Learning Systems Engineer on the Horizons team, focusing on building software infrastructure for AI models to use tools effectively and measure performance. This involves extending the agent framework, creating evaluations, managing training data pipelines, and applying data science techniques to improve model capabilities. The role combines software development with empirical analysis to advance model performance and capabilities, working closely with research and production teams. | AgentEval Gate | 9 |
| Research Engineer / Scientist, Alignment Science - London Research Engineer/Scientist focused on AI safety and alignment, conducting experimental research to understand and steer the behavior of powerful AI systems. The role involves testing robustness of safety techniques, running multi-agent RL experiments, building tooling for evaluating jailbreaks, and contributing to research papers. Collaboration with Interpretability, Fine-Tuning, and Frontier Red Team is expected. | Post-trainEval Gate | 9 |
| TPU Kernel Engineer This role focuses on optimizing ML systems, particularly for TPUs, by designing and implementing kernels to improve performance for research, training, and inference. It involves low-level optimization and providing feedback on model performance impacts. | ServePost-train | 9 |
| Research Engineer, Knowledge Team Research Engineer focused on redesigning how Claude interacts with external data sources by designing new information architectures and training language models to use them. This includes performing finetuning and RL, building knowledge base eval sets, and designing/evaluating agentic search capabilities. | AgentPost-train | 9 |
| Machine Learning Systems Engineer, Encodings and Tokenization Machine Learning Systems Engineer focused on developing and optimizing encodings and tokenization systems for Anthropic's Finetuning workflows, acting as a bridge between Pretraining and Finetuning teams. This role is crucial for improving model training efficiency and performance, enabling researchers to experiment with new tokenization methods, and ensuring the reliability and interpretability of AI systems. | DataPost-train | 9 |
| Machine Learning Systems Engineer, RL Engineering This role focuses on building, maintaining, and improving the critical algorithms and infrastructure for training AI models, specifically using RLHF and other advanced techniques. The goal is to enhance the performance, robustness, speed, reliability, and usability of these training systems to enable breakthroughs in AI capabilities and safety. | Post-train | 9 |
| Research Manager, Production Model Training Research Manager for Anthropic's Applied Finetuning team, leading a team to train flagship production models (like Claude.AI) using techniques such as Constitutional AI and RLHF. Responsibilities include managing day-to-day execution, prioritizing work, coaching reports, and contributing technically to the team's efforts in post-training techniques, algorithm implementation, data mix experiments, evaluation design, and pipeline improvement. | Post-train | 9 |
| [Expression of Interest] Research Scientist / Engineer, Honesty Research Scientist/Engineer focused on honesty in language models, developing techniques to minimize hallucinations and enhance truthfulness. This involves data curation, classifier development, evaluation frameworks, RAG implementation, human feedback collection, prompting pipelines, RL environments, and tools for human evaluators. | Post-trainAgent | 9 |
| Model Behavior Architect, Alignment Finetuning Role focused on shaping AI system behavior for alignment with human values through prompt engineering, data generation, and rigorous testing. Involves evaluating model judgment in domains like honesty, character, and ethics, and collaborating with research teams. Requires experience in prompt engineering, AI output evaluation, and understanding of LLM training/RL concepts. | Post-trainEval Gate | 9 |
| Research Scientist, Societal Impacts Research Scientist focused on empirical studies of AI's societal impacts, developing measurement systems and evaluation frameworks, and translating insights into product/policy recommendations. This role involves both quantitative and qualitative methods, with a focus on areas like economics, well-being, education, and alignment. | Eval GateAgent | 9 |
| Research Scientist/Engineer, Alignment Finetuning Research Scientist/Engineer focused on developing and implementing novel finetuning techniques to train language models for better alignment with human values (honesty, character, harmlessness). This involves using synthetic data generation, advanced training pipelines, and creating evaluation frameworks to measure alignment properties. The role also includes integrating improvements into production models and automating/scaling team workflows. | Post-train | 9 |
| Team Manager, Alignment RL Manager for a team developing and implementing AI alignment techniques, focusing on improving model values and behavior for hard-to-evaluate tasks. The role involves driving execution of alignment initiatives, supporting team growth, and ensuring collaboration across research. Key activities include implementing and scaling techniques like oversight, synthetic data generation, and training models to assist in model training, aiming to accelerate the deployment of alignment advances into frontier models. | Post-trainData | 9 |
| Research Engineer, Tokens (Pre-training) Research Engineer focused on pretraining data for large-scale AI models. Responsibilities include understanding data trends, scaling laws, optimizing data mixes, exploring new data sources, building research tools for analysis, and effective data processing. Strong software engineering and empirical research skills are required. | Pretrain | 9 |
| Research Scientist, Frontier Red Team (CBRN, Biosecurity) Research Scientist focused on red-teaming AI models for biosecurity risks, involving fine-tuning, threat modeling, and developing novel evaluations. This role bridges AI safety research with domain expertise in biosecurity. | Eval GatePost-train | 9 |
| Research Scientist, Frontier Red Team (Autonomy) Research Scientist role focused on developing and productionizing advanced autonomy evaluations for AI Safety Level (ASL) determination of models. This involves risk and capability modeling, designing, implementing, and running large-scale experiments to evaluate autonomous capabilities and forecast future capabilities, with potential for people management. | Eval GateAgent | 9 |
| Research Engineer, Frontier Red Team (RSP Evaluations) Research Engineer focused on developing and running "gold standard" evaluations for catastrophic risks to ensure safe release of frontier AI models, aligning with the Responsible Scaling Policy (RSP). The role involves creating evaluation systems, collaborating with domain experts, building sandboxed testing environments, and informing critical deployment decisions. | Eval Gate | 9 |
| Research Engineer / Scientist, Safeguards Research Engineer/Scientist focused on AI safeguards, conducting critical safety research and engineering for reliable, interpretable, and steerable AI systems. The role involves testing robustness of safety techniques, running multi-agent RL experiments (AI Debate), building tooling for evaluating jailbreaks, and producing evaluation questions for model reasoning in safety-relevant contexts. It bridges research and engineering, with a focus on both immediate and long-term AI safety challenges, including risks from advanced systems and current threats. | Post-trainAgent | 9 |
| Research Engineer, Societal Impacts Research Engineer focused on building infrastructure for foundational research into AI's societal impact. This involves designing and implementing scalable systems for experiments, evaluations, and data processing, with a strong emphasis on reliability and supporting future research directions. The role requires close collaboration with researchers and policy experts to generate insights and inform strategy. | Eval Gate | 9 |
| Research Manager, Horizons Research Manager for the Horizons team at Anthropic, focusing on RL with LLMs, code generation, reasoning, tool use, and agents. The role involves team management, project planning, vision-setting, people development, and ensuring execution aligns with AI safety goals. | Pretrain | 9 |
| Research Engineer, Machine Learning (Horizons) Research Engineer focused on advancing LLM capabilities and safety through fundamental research in reinforcement learning, improving reasoning (code, math), and exploring RL for agentic tasks. Involves developing novel RL techniques, creating tools for models to interact with, and designing experiments. | Post-trainAgent | 9 |
| Research Engineer, Knowledge Team Research Engineer focused on redesigning how LLMs interact with external data sources by designing new information architectures and training models to use them. Responsibilities include implementing information architecture strategies, performing finetuning and RL, building knowledge base eval sets, and designing agentic search capabilities. Requires strong Python, ML research experience, and experience with LLMs. Experience with complex agentic systems, RAG, and distributed information retrieval is a plus. | AgentPost-train | 9 |
| Research Engineer, Agents Research Engineer focused on advancing agentic AI systems, involving finetuning Claude for agentic tasks, developing tools for agents (memory, communication), prompt engineering, automated evaluation, and optimizing data mixes for model training. The role also involves creating and maintaining infrastructure for prompt iteration and testing. | AgentPost-train | 9 |
| Product Manager, Safeguards Rare Harms Product Manager for Anthropic's Safeguards team, focusing on building and deploying systems to ensure AI safety and prevent misuse. This role involves ideation, design, development, and UX for safeguards, working closely with research and product teams to mitigate risks associated with frontier models across various platforms. | Eval GateAgent | 8 |
| Engineering Manager, Cloud Safety Engineering Manager to lead the Cloud Safety team, responsible for scaling and optimizing Claude's serving infrastructure across Cloud Service Providers (CSPs). The role involves owning end-to-end safety, including API, inference, classifiers, fraud detection, data management, and operations, to ensure safe usage and enable the launch of new models and features at scale. | Serve | 8 |
| Applied AI Architect Lead, EMEA Commercial Lead a team of Applied AI Architects in EMEA to drive the adoption of Anthropic's AI products (Claude for Enterprise, Claude Code, API) across commercial accounts. This player-coach role involves managing a team, owning technical wins on key accounts, developing go-to-market strategies with sales, and ensuring customer success through technical expertise and consultative sales. | Ship | 8 |
| Applied AI Engineer Applied AI Engineer role focused on being a technical advisor to customers deploying Claude (LLM). Responsibilities include guiding architecture, developing evaluation frameworks, and implementing cutting-edge LLM patterns via API. Requires strong Python skills and production experience with LLMs, including agent development and retrieval frameworks. | Agent | 8 |
| Data Operations Manager, Human Data This role focuses on building and scaling data operations for research teams working on frontier AI capabilities, including RLHF, safety, tool use, and agentic workflows. The Data Operations Manager will own data strategy, manage vendor partnerships, and implement systems to ensure high-quality training data, directly impacting model performance on critical capabilities. | DataPost-train | 8 |
| Product Engineer, Computer Use Product Engineer role focused on building and shipping AI-powered computer-use and browser-control product surfaces. This involves full-stack development, agent harness, and working with LLM APIs and agent frameworks. The role requires end-to-end ownership and iteration based on user feedback, with a focus on reliability and robustness of the agent harness. | Agent | 8 |
| Applied AI Architect (Startups) This role focuses on partnering with startups to help them build and scale AI solutions using Anthropic's Claude Developer Platform. The architect will guide technical decisions, win evaluations, and provide feedback to product and engineering teams. Requires strong technical expertise in LLM application development and deployment, with a customer-facing background. | Agent | 8 |
| Software Engineer, RL Data Software Engineer on the RL Data team responsible for building systems that produce high-quality reinforcement learning data for Claude. This includes data collection pipelines, human feedback tooling, execution environments, and quality assurance. The role involves end-to-end ownership of stack components, iterating on prompts and evals, developing QA frameworks, hardening execution environments, and collaborating with domain experts and operations partners. | DataPost-train | 8 |
| Engineering Manager, Cybersecurity Products Engineering Manager for AI-powered cybersecurity products, leading a team to prototype and ship products using frontier models. The role involves setting technical direction, partnering with research, and staying close to customers. It requires hands-on technical involvement, product instincts, and scaling the team. | AgentShip | 8 |
| Software Engineer, Claude Design Software Engineer to build and shape Claude Design, a product that lets users collaborate with Claude to create visual work. This is a frontend-leaning role focused on creating intuitive AI-generated design experiences, working closely with researchers and users to iterate and validate product concepts. | ShipAgent | 8 |
| Manager of Applied AI Architecture, Startups Manager of Applied AI Architecture for startups, leading a team of technical architects to drive adoption of frontier AI and help startups build AI-native products using the Claude Developer Platform. Focuses on technical partnership, building teams, defining playbooks, and influencing product roadmap. | Agent | 8 |
| Engineering Manager, Research Tools Engineering Manager for Anthropic's Research Tools team, focusing on building and improving systems for large-scale, distributed finetuning runs and enhancing researcher productivity. The role involves prioritizing team work, designing operational processes, coaching reports, and managing recruiting efforts to support rapid growth in AI model development and research. | Post-train | 8 |
| Manager of Applied AI Architecture, Enterprise Tech (Cyber) Manager of Applied AI Architecture, Enterprise Tech (Cyber) at Anthropic, responsible for leading a team that drives the adoption of Anthropic's AI products (Claude for Enterprise, Claude Code, API) within Enterprise Tech companies. This role involves technical guidance, pre-sales engagements, customer strategy, and ensuring the safe and reliable deployment of AI systems. | ShipAgent | 8 |
| Technical Specialist, Claude Code This role focuses on driving adoption of Anthropic's AI products (Claude Code, Claude Enterprise) within enterprise customers. It involves technical enablement, delivering workshops, building demo apps, and supporting strategic pilots, acting as a trusted technical voice to developers and leaders. The role bridges pre-sales and post-sale engagement to ensure deep integration and usage of AI capabilities. | Agent | 8 |
| Applied AI Architect, Startups This role is for an Applied AI Architect on the Startups Applied AI team. The primary responsibility is to act as a technical partner for startups, helping them build on Anthropic's Claude Developer Platform. This involves architecting LLM solutions, winning technical evaluations, and guiding customers from discovery through deployment. The role requires deep technical expertise in building and deploying LLM-powered applications, understanding AI engineering best practices, and communicating complex AI concepts to technical founders and engineering teams. | Agent | 8 |
| Full-Stack Software Engineer, Reinforcement Learning Full-Stack Software Engineer to build platforms, tools, and interfaces for environment creation, data collection, and training observability for RL. The role involves owning product surfaces end-to-end, iterating on data collection strategies, and partnering with researchers to ship reliable products. | DataEval Gate | 8 |
| Anthropic Fellows Program — ML Systems & Performance This is a research fellowship program focused on AI systems and performance, with the goal of producing public outputs like paper submissions. Fellows will work on empirical projects, potentially involving building ML systems, data pipelines, or infrastructure for accelerators, using external infrastructure and open-source models. | Data | 8 |
| Manager of Applied AI Architecture, Partnerships Manager of Applied AI Architecture, Partnerships role at Anthropic, focused on driving adoption of frontier AI products (Claude for Enterprise, Claude Code, API) through system integrators and cloud partners. Responsibilities include leading a team of Partner Solutions Architects, establishing pre-sales engagement processes, co-building partner strategy, enabling partner AI practices, developing joint solutions, and supporting partner-led pre-sales engagements. Requires technical depth in enterprise AI deployments and experience managing technical teams. | Ship | 8 |
| Staff Software Engineer, Cloud Inference Safeguards Staff Software Engineer to build and operate safety, oversight, and intervention mechanisms for AI models (Claude) on third-party cloud service provider (CSP) platforms. This role ensures requests are monitored for misuse, enforced against policy, and compliant with data residency and privacy commitments. The engineer will integrate Safeguards into the CSP inference serving path, focusing on real-time enforcement, telemetry, and privacy architecture, while maintaining serving-path latency and scale. The work directly impacts the ability to ship frontier models on CSP platforms safely. | ServeEval Gate | 8 |
| Engineering Manager, Agent Prompts & Evals Engineering Manager to lead the Agent Prompts & Evals team, responsible for the infrastructure that enables shipping model and prompt changes with confidence. This includes eval frameworks, system prompt pipelines, and regression-detection systems. The team acts as a platform for model behavior, sitting between product engineering and research, and partners with other evals groups and product teams. The role requires leading and growing a team, owning the product-side eval platform and system prompt infrastructure, managing model launches, fostering collaboration, recruiting engineers, and shaping team investment in areas like frontier eval development and launch automation. | Eval GateAgent | 8 |
| Technical Deployment Lead Technical Deployment Lead responsible for delivering customized AI agent solutions to enterprise clients in highly regulated industries. This role involves managing end-to-end engagements, from scoping and technical discovery to production launch, and requires strong client-facing and technical leadership skills to guide the deployment of AI agents within critical business processes. | Agent | 8 |
| Applied AI Engineer, Beneficial Deployments Applied AI Engineer role focused on deploying AI to mission-driven organizations, advising on evals and agent architectures, building ecosystem tooling, and prototyping new agents. Requires production experience with LLM applications and a builder mindset. | AgentEval Gate | 8 |
| Sr. Software Engineer, Inference Software Engineer focused on building and maintaining the critical systems that serve Claude to millions of users worldwide. Responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators, maximizing compute efficiency and enabling research. | Serve | 8 |
| Staff Software Engineer, Inference Staff Software Engineer on the Inference team responsible for building and maintaining systems that serve Claude to millions of users. Focuses on maximizing compute efficiency and providing high-performance inference infrastructure for research, tackling complex distributed systems challenges across diverse AI accelerators. | Serve | 8 |