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 |
|---|---|---|
| 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, 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 |
| 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 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 |