Anthropic currently has 151 active AI-related job listings, with a significant focus on roles related to agents, which constitute 32% of their openings. Engineering is the most frequent function, followed by Research. The majority of their hiring is concentrated in the United States. Frequent technical tags include evals, model_serving, and agent_orchestration, suggesting a focus on the practical deployment and management of AI systems.
Currently tracking 127 active AI roles, down 32% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $46k–$850k (avg $406k).
Anthropic currently has 149 active AI-related roles in our index. The most common open titles are: 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), Product Manager, Safeguards Rare Harms. Most positions are in Engineering and Research.
Anthropic's active AI hiring is concentrated in: agents (31%), serving infrastructure (15%), post-training (15%). 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 (130 roles), United Kingdom (18 roles), Canada (6 roles), Ireland (3 roles).
Job postings at Anthropic most frequently mention: Machine Learning, AI Safety, Production ML Systems, System Design, Large Language Models (LLMs).
In the past 30 days, Anthropic has posted 24 new AI-related roles. That is a -27% change versus the prior 30 days (33 → 24).
| Title | Stage | AI score |
|---|---|---|
| Anthropic STEM Fellow This role is for a STEM Fellow to work alongside Anthropic's research teams for a few months. Fellows will use their domain expertise to evaluate, improve, and apply Claude's capabilities in their field. This involves designing evaluations, identifying data/techniques for capability gaps, and applying Claude to open problems using various strategies and tools. Projects are scoped to ship within the fellowship period. | Eval GateAgent | 9 |
| Manager of Forward Deployed Engineering Manager of Forward Deployed Engineering at Anthropic, responsible for leading a team that embeds with strategic customers to ship production AI applications and agent deployments built on Claude. This player-coach role involves hiring, developing, and mentoring engineers, overseeing customer engagements, reviewing technical architectures, and collaborating with cross-functional teams to drive AI transformation for enterprise clients. |
| Agent |
| 9 |
| Anthropic Fellows Program — Reinforcement Learning This is a research fellowship program focused on Reinforcement Learning (RL) within AI safety. Fellows will work on empirical projects, potentially using external infrastructure, with the goal of producing public outputs like paper submissions. The program emphasizes mentorship from Anthropic researchers and provides a stipend and compute funding. Key activities include building model-based tools for data quality, understanding generalization, and creating RL environments for capabilities and safety tasks. | Post-train | 9 |
| Anthropic Fellows Program — AI Safety This is a research fellowship program focused on AI safety, aiming to foster talent in empirical AI research. Fellows will work on projects aligned with Anthropic's research priorities, using external infrastructure and external models, with the goal of producing public outputs like paper submissions. Key research areas include Scalable Oversight, Adversarial Robustness and AI Control, Model Organisms, Model Internals / Mechanistic Interpretability, and AI Welfare. | Post-train | 9 |
| Research Engineer, Performance RL Research Engineer focused on Reinforcement Learning for code generation and accelerator performance, aiming to improve model reasoning and coding capabilities. The role involves inventing RL environments, conducting experiments, shaping research roadmaps, and delivering work into training runs, with a strong emphasis on collaboration and scaling research innovations. | Post-trainData | 9 |
| Security Labs Engineer This role focuses on executing security R&D projects end-to-end, building novel security infrastructure, and driving successful experiments toward production scale. It involves working with research teams to test security controls, evaluating new security technologies, and documenting results to inform future security architecture. The role spans from initial project scoping to potential production deployment, with a focus on high-assurance environments and AI-assisted security tooling. | ServeShip | 9 |
| Research Lead, Training Insights Research Lead focused on developing and executing strategies for measuring and characterizing model capabilities across training and deployment. This role involves driving original research into new evaluation methodologies, leading a team, and spanning the full lifecycle of model development, from pretraining to deployment. The work includes creating long-horizon evaluations, measuring emerging capabilities, and understanding their development during RL training and post-training. The role also involves cross-organizational collaboration to map evaluation landscapes and identify gaps, shaping the evaluation narrative for model releases, and contributing to the broader research community. | Eval GatePost-train | 9 |
| Research Engineer, AI Observability Research Engineer focused on designing and building AI-based monitoring systems to analyze large unstructured datasets, produce structured insights, and develop agentic integrations for investigation and action. The role involves working across the full stack, from core analysis frameworks to user-facing applications, with a direct impact on measuring and mitigating AI misuse and misalignment. This role is critical for scaling human oversight of AI systems. | Eval GateAgent | 9 |
| Forward Deployed Engineer The Forward Deployed Engineer (FDE) role at Anthropic focuses on embedding with strategic customers to drive the adoption of advanced AI applications. This role involves building production applications using Claude models within customer systems, delivering technical artifacts like sub-agents and agent skills, and providing deployment support. The FDE will work closely with post-sales, product, and engineering teams, combining engineering expertise with customer-facing skills to solve complex business challenges and represent Anthropic's mission. | Agent | 9 |
| Product Management, Research Product Manager for Anthropic's Research team, focusing on ideation and deployment of new models and products. This role bridges applied research with customer needs, identifying and productizing frontier AI capabilities into new product categories. Requires a strong technical background in AI/ML and experience launching and scaling products. | Post-trainPretrain | 9 |
| Research Engineer, Environment Scaling This role focuses on improving the intelligence of public models by building and managing RL training environments. It involves identifying tasks, designing reward signals, managing external data vendors, and evaluating model performance, combining ML research, data operations, and project management. | DataPost-train | 9 |
| Research Engineer, Production Model Post-Training Research Engineer focused on post-training of production LLMs, implementing and optimizing techniques like Constitutional AI and RLHF to enhance model capabilities, alignment, and safety. Involves research, pipeline development, evaluation, and debugging at scale. | Post-train | 9 |
| Prompt Engineer, Agent Prompts & Evals This role focuses on prompt engineering and evaluation development for AI-first products and features, bridging model capabilities with user experience. It involves designing, testing, and optimizing prompts, building evaluation suites, supporting model launches, and contributing to prompt development frameworks. The role requires strong software engineering skills, LLM and prompt engineering experience, and understanding of evaluation methodologies. | AgentEval Gate | 9 |
| Research Scientist, Frontier Red Team (Emerging Risks) Research Scientist focused on understanding and defending against societal risks from advanced AI models, particularly self-improving and autonomous systems. The role involves designing research experiments, building evals, and producing artifacts to communicate model capabilities and inform product/safeguards decisions. Emphasis on emerging risks from AI integration into the economy and society. | Eval GateAgent | 9 |
| Model Quality Software Engineer, Claude Code Staff Software Engineer to set technical direction at the intersection of engineering and research on the Claude Code team. Architect systems, tooling, and evaluation infrastructure to measure, understand, and improve Claude's coding capabilities. Drive architecture, mentor engineers, and influence the direction of Claude Code. | Eval GateAgent | 9 |
| Research Product Manager, Labs This role is for a Research Product Manager in Anthropic's Labs team, focusing on 0-to-1 product development. The individual will bridge pure research and product experimentation, identifying and defining new product categories enabled by AI. Responsibilities include understanding emerging research, identifying capabilities for new products, building prototypes, leading product strategy and execution for experimental initiatives, and validating product-market fit. The role requires a deep technical background, experience launching new products, and the ability to navigate ambiguity. | ShipPretrain | 9 |
| Research Engineer / Scientist, Frontier Red Team (Cyber) Research Engineer/Scientist focused on AI-enabled cybersecurity, developing tools and frameworks for autonomous vulnerability discovery, remediation, malware detection, and pentesting. Designs and runs experiments to evaluate AI cyber capabilities and builds infrastructure for AI systems operating in security environments. Translates findings into demonstrations for policymakers and collaborates with external experts. Senior candidates will set research strategy and own the technical roadmap. | AgentEval Gate | 9 |
| Research Engineer, Frontier Red Team (Hardware Lead) Research Engineer focused on leading hardware research for frontier AI safety, specifically interfacing LLMs with robotics and cyberphysical systems. The role involves designing and building systems, developing evaluations, creating training environments, and demonstrating capabilities to inform policy and build defenses against advanced AI risks. | AgentEval Gate | 9 |
| Applied AI Engineer, Startups Applied AI Engineer role focused on advising and partnering with AI-native startups to build on the Claude Developer Platform. Responsibilities include technical guidance, developing evaluation frameworks, designing scalable architectures, and creating technical resources to help startups succeed with Claude. Requires production experience with LLM-powered applications, agent architectures, and evaluation frameworks. | Agent | 9 |
| Research Engineer / Research Scientist, Vision Research Engineer/Scientist focused on vision and spatial reasoning for LLMs, working on pretraining, RL, and runtime techniques like agentic harnesses. Involves developing and evaluating multimodal capabilities, creating benchmarks, and partnering with product teams to improve Claude models. | Post-trainAgent | 9 |
| Research Engineer/Research Scientist, Audio Research Engineer/Scientist focused on audio AI, working on training audio models, developing novel architectures, and optimizing inference for speech and audio understanding and generation systems. | Post-trainServe | 9 |
| Applied Safety Research Engineer, Safeguards Research-oriented engineer to develop methods for representative, robust, and informative AI safety evaluations. This role involves designing experiments to improve model behavior evaluation, shipping these methods into pipelines that inform model training and deployment, and directly shaping how Anthropic understands and improves model safety across misuse, prompt injection, and user well-being. The role also involves building tooling for policy experts and surfacing findings to drive upstream model improvements. | Eval GatePost-train | 9 |
| Research Engineer, Universes Research Engineer role focused on building next-generation agentic environments for training AI models. This role involves implementing novel approaches, contributing to research direction, designing training environments and methodologies, and building evaluations for capable and safe agentic AI. It blends research and engineering, with a focus on reinforcement learning and complex, long-horizon agentic tasks. | AgentPost-train | 9 |
| Senior Research Scientist, Reward Models Senior Research Scientist focused on reward models for LLMs, involving novel architectures, RLHF, LLM-based evaluation, and mitigating reward hacking. Aims to improve model alignment with human values and translate research into production systems. | Post-trainEval Gate | 9 |
| Research Engineer, Reward Models Platform Research Engineer focused on building platforms and infrastructure to automate and accelerate the reward model development and evaluation workflows for ML researchers at Anthropic. The role involves creating tools for rubric development, human feedback analysis, reward robustness evaluation, and detecting reward hacks, with the goal of enabling rapid iteration and improving reward signal quality for training AI models. | Post-train | 9 |
| Anthropic Fellows Program — AI Security This is a research fellowship program focused on AI safety and security, aiming to produce public outputs like paper submissions. Fellows will use external infrastructure and open-source models, working on empirical projects with mentorship from Anthropic researchers. | Post-train | 9 |
| Anthropic Fellows Program Anthropic's Fellows Program offers a 4-month full-time research opportunity focused on AI safety and related areas. Fellows will use external infrastructure and open-source models to conduct empirical projects, aiming for public outputs like paper submissions, with mentorship from Anthropic researchers. The program is designed to foster AI research and engineering talent, regardless of previous experience, and emphasizes safety, interpretability, and steerability of AI systems. | Pretrain | 9 |
| Research Engineer, Cybersecurity Reinforcement Learning Research Engineer role focused on applying reinforcement learning to cybersecurity tasks like secure coding and vulnerability remediation, blending research and engineering to train safe AI models. Requires cybersecurity domain expertise and ML/software engineering skills. | Post-trainData | 9 |
| Cross-functional Prompt Engineer This role focuses on shaping and owning the behavior of Claude, Anthropic's AI model, across all products. It involves authoring system prompts, developing meta-prompts for research pipelines, leading incident response for behavioral issues, and scaling best practices. The role requires strong prompting skills, technical foundations, excellent judgment, and collaboration across research, product, and safety teams. It sits at the intersection of research and product, aiming to ensure AI systems are safe, beneficial, and aligned with human values at scale. | Post-trainAgent | 9 |
| Forward Deployed Engineer Forward Deployed Engineer (FDE) embeds with strategic customers to drive AI adoption by shipping advanced AI applications built on Claude models. Collaborates with customer teams, Post-Sales, Product, and Engineering to solve business challenges using frontier AI, focusing on safety and reliability. Operates autonomously, builds customer relationships, and identifies new AI deployment opportunities. | Agent | 9 |
| Research Engineer, Model Evaluations Research Engineer focused on designing and implementing Anthropic's model evaluation platform, shaping how models are understood, measured, and improved. This role involves leading the architecture of scalable evaluation infrastructure, implementing high-throughput pipelines for production training, analyzing results to guide model development, and collaborating with research and training teams. The goal is to ensure models meet high standards for capabilities and safety before deployment, influencing training decisions and the overall model roadmap. | Eval GatePost-train | 9 |
| Research Engineer, Model Evaluations Research Engineer focused on designing and implementing Anthropic's model evaluation platform, influencing training decisions and model development. This role involves leading the architecture of scalable evaluation pipelines, analyzing results, partnering with research teams, and contributing to publications. It sits at the intersection of research and engineering, with a strong emphasis on AI safety and model capabilities. | Eval GatePost-train | 9 |
| Research Engineer, Production Model Post-Training, London Research Engineer focused on post-training of production AI models, including techniques like Constitutional AI and RLHF. The role involves implementing, scaling, and optimizing these processes, conducting research to improve model quality, and developing pipelines for fine-tuning and evaluation. Requires strong software engineering skills, experience with large-scale distributed systems, and familiarity with training/fine-tuning/evaluating LLMs. The role directly impacts the quality, safety, and capabilities of production models. | Post-trainServe | 9 |
| Research Engineer, Interpretability Research Engineer focused on building and maintaining specialized infrastructure for interpretability research in AI systems. This involves developing tools for model analysis, optimizing training and inference pipelines, and ensuring reliability for safety audits, with a strong emphasis on understanding and controlling model behavior. | Post-trainServe | 9 |
| Staff Infrastructure Engineer, Pre-training Staff Infrastructure Engineer focused on the data processing infrastructure for large language model pre-training. This role involves designing, implementing, and optimizing scalable systems for data quality, validation, and distributed computing at web-scale, collaborating closely with research teams. | Data | 9 |
| Research Engineer, Virtual Collaborator (Cowork) Research Engineer focused on training Claude for virtual collaborator workflows, involving RL environments, data creation, and evaluation systems for enterprise use cases. | Post-trainData | 9 |
| Machine Learning Systems Engineer, RL Engineering ML Systems Engineer focused on Reinforcement Learning Engineering to build, maintain, and improve the algorithms and infrastructure for training AI models like Claude using RLHF and other advanced techniques. The role emphasizes improving system performance, robustness, and usability to accelerate research breakthroughs in AI capabilities and safety. | Post-train | 9 |
| Machine Learning Systems Engineer, Research Tools Machine Learning Systems Engineer focused on developing and optimizing encodings and tokenization systems for Anthropic's Finetuning workflows. This role acts as a bridge between Pretraining and Finetuning teams, building infrastructure crucial for model learning and data interpretation, impacting research progress and efficiency. | DataPost-train | 9 |
| Research Engineer / Research Scientist, Tokens Research Engineer/Scientist role focused on building large-scale ML systems, touching all parts of code and infrastructure, from cluster reliability and job efficiency to running scientific experiments and improving dev tooling. The role involves optimizing ML systems, comparing model variants, scaling training jobs, and designing fault tolerance strategies, with a focus on safe, steerable, and trustworthy AI. | PretrainServe | 9 |
| ML/Research Engineer, Safeguards ML/Research Engineer focused on detecting and mitigating misuse of AI systems, building classifiers, monitoring for harms, evaluating agentic product safety, and conducting research on red-teaming and adversarial robustness. | AgentData | 9 |
| Research Operations & Strategy Lead - Coding & Cybersecurity Data This role focuses on building and scaling data operations for AI models, specifically for coding and cybersecurity capabilities. The lead will partner with research teams to design and execute data strategies, manage vendors, and oversee the data pipeline from requirements to production. While not hands-on engineering, technical depth in understanding training data quality is required, with a focus on strategy and execution. | DataAgent | 9 |
| Data Operations Manager - Computer Use & Tool Use This role focuses on building and scaling data operations for AI models, specifically for computer use capabilities and tool use safety. The manager will partner with research teams to design and execute data strategies, manage vendors, and own the data pipeline from requirements to production. The goal is to ensure AI models can use tools safely and operate computers autonomously, impacting agentic workflows. The role requires technical depth in ML workflows and RL environments, strategic thinking, and operational excellence. | DataAgent | 9 |
| Privacy Research Engineer, Safeguards Research Engineer focused on privacy for large language models, developing and auditing privacy-preserving training algorithms and techniques, and ensuring responsible data handling. | DataPost-train | 9 |
| Research Engineer, Pretraining Scaling - London Research Engineer focused on pretraining and scaling large language models, involving performance optimization, debugging, experimental design, and ensuring reliability of production training pipelines. The role is highly operational, requiring on-call incident response during model launches, and involves building and maintaining training infrastructure and codebase capabilities. | Pretrain | 9 |
| Research Engineer / Research Scientist, Biology & Life Sciences Research Engineer/Scientist role focused on applying AI/ML to accelerate progress in life sciences. The role involves developing novel evaluation frameworks and training strategies to improve AI model performance on biological research tasks, bridging domain expertise with ML engineering. It emphasizes rigorous methods, collaboration, and safety. | Post-trainEval Gate | 9 |
| Research Engineer / Scientist, Tool Use Safety Research Engineer/Scientist focused on advancing the frontier of safe tool use in AI models, specifically addressing prompt injection, data exfiltration, adversarial attacks, and autonomous agent behavior with large tool sets. The role involves designing and implementing RL methodologies, building evaluations, and shipping research advances into production models, with a strong emphasis on safety and reliability. | AgentPost-train | 9 |
| Performance Engineer, GPU This role focuses on optimizing GPU performance and systems engineering for large language models, specifically improving utilization and efficiency for inference and training at scale. It involves deep work in GPU programming, custom kernel development, and distributed systems. | ServePretrain | 9 |
| Research Engineer / Scientist, Robustness Research Engineer/Scientist focused on AI robustness and safety within the Alignment Science team. The role involves conducting critical safety research and engineering to ensure AI systems can be deployed safely, with projects spanning jailbreak robustness, automated red-teaming, monitoring techniques, and applied threat modeling. It emphasizes pragmatic approaches to AI safety challenges, understanding and steering AI behavior, and contributing to research papers and safety efforts. | Post-trainAgent | 9 |
| Research Engineer / Scientist, Tool Use Research Engineer/Scientist focused on advancing the frontier of tool use for AI agents, aiming to improve accuracy, reliability, safety, and efficiency in complex workflows. The role involves defining research agendas, designing RL methodologies, building evaluations, and shipping research advances into production models, with a strong emphasis on safety and collaboration. | AgentPost-train | 9 |
| Research Engineer, Model Performance & Quality Research Engineer focused on systematically understanding and monitoring model quality in real-time. This role involves training production models, developing monitoring systems, and creating novel evaluation methodologies, bridging research and production across the model training pipeline. | Eval GatePost-train | 9 |