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.
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).
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).
| Title | Stage | AI score |
|---|---|---|
| Staff+ Software Engineer, Inference Runtime Staff+ Software Engineer for Anthropic's Inference Runtime team, focusing on the accelerator-agnostic core of their AI inference serving stack. The role involves setting technical direction, owning the architecture and roadmap, hands-on coding in Rust/Python, optimizing accelerator usage, and building validation systems. Requires deep systems engineering or ML infrastructure background with experience in performance optimization and large-scale distributed systems. | Serve | 9 |
| Software Engineer, Safeguards Evals Software Engineer role focused on building and owning the evaluation infrastructure for an agentic investigation system. This involves designing experiments, constructing high-quality eval datasets, measuring agent performance, analyzing coverage gaps, and productionizing research into release pipelines. The role also involves building tooling for policy experts and constructing RL environments to improve safety investigation capabilities. |
| AgentEval Gate |
| 9 |
| Research Engineer, Machine Learning (RL Velocity) Research Engineer focused on building and improving the RL training infrastructure and tooling at Anthropic. The role involves identifying and removing bottlenecks in the RL stack, partnering with researchers and other engineering teams, and owning the reliability and performance of research runs to enable faster iteration and shipping of better models at scale. | DataPost-train | 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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, 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 |
| 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, 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 |
| 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 |
| 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 |
| 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, CLIO Machine Learning Systems Engineer to join the Encodings and Tokenization team, focusing on developing and optimizing tokenization systems for Pretraining and Finetuning workflows. This role builds infrastructure impacting model learning and data interpretation, bridging Pretraining and Finetuning teams. | DataPost-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. This role acts as a bridge between Pretraining and Finetuning teams, building infrastructure that impacts how models learn from data and improving training efficiency. Requires strong software engineering and ML expertise, with experience in ML systems, data pipelines, or ML infrastructure. | DataPost-train | 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 |
| Data Operations Manager, Knowledge Lead human data collection initiatives to power advanced AI capabilities, focusing on AI safety and capability research. Design and build novel data collection systems and evaluation frameworks, translating research into scalable data systems. This is a 0-to-1 role requiring operational excellence at the intersection of AI research and execution. | DataEval Gate | 9 |
| Data Operations Manager, Horizons This role leads human data collection initiatives to power advanced AI research, focusing on agentic AI systems, coding, and computer use capabilities. It involves designing and building scalable data collection methodologies and systems from scratch, acting as a 'data as the product' owner for critical AI research. The role requires a strong software engineering background with entrepreneurial experience, technical depth in ML workflows, and project management skills. | DataAgent | 9 |
| Engineering Manager, GPU (ML Accelerator) Engineering Manager for Anthropic's performance and scaling teams, focusing on optimizing compute resources for inference and training systems. The role involves leadership, technical contribution, bottleneck identification, and ensuring efficiency in large-scale ML systems, with a strong emphasis on GPU/accelerator programming and ML/OS internals. | ServeData | 9 |
| Engineering Manager, ML Performance and Scaling Engineering Manager for ML Performance and Scaling teams, focusing on optimizing inference and training systems, identifying bottlenecks, and maximizing efficiency. Requires management experience, background in ML/AI, and interest in safe AI development. | ServePost-train | 9 |
| TPU Kernel Engineer TPU Kernel Engineer responsible for identifying and addressing performance issues across ML systems (research, training, inference), with a focus on designing and optimizing kernels for TPUs. Provides feedback to researchers on model performance impact. | ServePost-train | 9 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| Engineering Manager, Cloud Inference AWS Engineering Manager to lead the Cloud Inference team for AWS, responsible for scaling and optimizing Claude's inference, API, load balancing, capacity, and operations on AWS. The role ensures LLMs meet performance, safety, and security standards, and enhances global inference technology deployment. It focuses on increasing operational scale and accelerating the launch of new models and features. | Serve | 8 |
| Engineering Manager, Vertical AI Products (Multiple Roles) Engineering Manager for Vertical AI Products at Anthropic, focusing on building and shipping AI products for specific industries like financial services, life sciences, and healthcare. The role involves leading engineering teams, defining products, working with enterprise customers, and collaborating with research to improve AI models. The teams are often building products from scratch (0->1) or scaling existing ones. | ShipAgent | 8 |