Anthropic
AI Frontier · AI lab
- HQ
- San Francisco, US
- Founded
- 2021
- Size
- 1,500+
- Website
- anthropic.com
- Blog
- anthropic.com
Products
AI Frontier · AI lab
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 32 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Evals Infrastructure Tech Lead / Manager Lead the team building and scaling the distributed systems that orchestrate, schedule, and execute evals for frontier models, ensuring measurement quality, reproducibility, and that eval signal reaches decision-makers. This role involves managing engineers and contributing directly as an engineer, focusing on inference, research, and infrastructure engineering. | Eval GateServe | 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. |
| 9 |
| ML Infrastructure Engineer, Safeguards ML Infrastructure Engineer focused on building and scaling critical infrastructure for AI safety systems, including real-time and batch classifier/safety evaluations, monitoring, and optimizing inference for safety-critical applications. | Eval GateServe | 9 |
| 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 |
| Machine Learning Systems Engineer, Model Evaluations This role focuses on building and maintaining the infrastructure for Model Evaluations and Research Inference, enabling researchers to systematically test and assess model capabilities. It involves designing scalable systems, optimizing APIs, creating data pipelines, and implementing monitoring for research-focused inference systems. The goal is to accelerate the model development lifecycle and support Anthropic's mission of creating safe and beneficial AI. | Eval GateServe | 8 |
| Machine Learning Systems Engineer, Model APIs Machine Learning Systems Engineer focused on building and maintaining Model Evaluations infrastructure and Research Inference APIs/infrastructure to enable researchers to effectively evaluate models and conduct inference tasks, directly impacting AI advancement. | Eval GateServe | 8 |
| Safeguards Enforcement Analyst, Violence & Extremism This role focuses on building and executing operational workflows to assess AI model behavior, drive enforcement decisions, and develop evaluations for violence and extremism policy areas. It involves designing automated enforcement systems, creating evals to measure model performance, and partnering with engineering and data science teams to optimize detection and enforcement. The role also requires reviewing flagged content, identifying misuse patterns, and staying updated on emerging threats and AI policy enforcement best practices. | Eval GateAgent | 7 |
| Software Engineer, Safeguards Infrastructure Software Engineer focused on building foundational systems for AI safety, including infrastructure for data management, metric and evaluation systems, and tooling for human and agentic review. The role involves ensuring the day-to-day running of Safeguards systems and building robust, reliable multi-layered defenses for real-time improvement of safety mechanisms at scale. | Eval GateAgent | 7 |