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, Domain Scaling Research Engineer focused on scaling AI models for real-world knowledge work in domains like finance, healthcare, and legal. This role involves owning the end-to-end data strategy, from sourcing tasks to RL training, including designing reward signals, managing external data vendors, and developing QA frameworks to ensure environment quality and prevent reward hacking. It combines applied research with hands-on data work. | DataPost-train | 9 |
| Research Engineer, Machine Learning (RL Velocity) The RL Velocity team owns the efficiency and reliability of the RL Science stack, building and improving the core platform for RL training runs to remove bottlenecks and enable faster iteration. This role focuses on ML infrastructure, distributed systems, and research tooling to improve the velocity and reliability of RL training at scale. |
| DataPost-train |
| 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 |
| 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 |
| 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, 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 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, 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 |
| 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 |
| 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, 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 |
| 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 |
| 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 |
| 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 |
| Full Stack Software Engineer, Reinforcement Learning Full-Stack Software Engineer to build platforms, tools, and interfaces for Reinforcement Learning environment creation, data collection, and training observability. This role supports researchers, vendors, and data labelers in generating high-quality training data for frontier models. Requires strong full-stack engineering skills and ability to build reliable products. | DataEval Gate | 8 |
| Research Engineer, Data Ingestion Research Engineer role focused on building and scaling a large-scale web crawler for data ingestion, with a focus on data quality evaluation and improvement to support the creation of pretrained models. | Data | 8 |
| Regional Research Economist, Economic Research This role focuses on researching and measuring the economic impact of AI in a specific region, collaborating with various stakeholders to develop methodologies and translate insights into policy recommendations. It involves using frontier methods in econometrics and machine learning, and contributing to datasets tracking AI's impact on labor markets and productivity. | Data | 7 |
| Regional Research Economist, Economic Research Research Economist focused on measuring and understanding AI's economic impact, developing new methodologies, and collaborating with external partners on policy interventions. Utilizes frontier econometrics, machine learning, and structural estimation methods. | Data | 7 |
| Product Management, Human Data Platform Product Manager for Anthropic's Human Data Platform, focusing on building systems to collect data that improves AI models. Responsibilities include owning product direction for data tooling, partnering with engineering, understanding research and training approaches, identifying patterns for reusable infrastructure, understanding vendor pain points, and defining KPIs related to data collection and model impact. | Data | 7 |
| Anthropic Fellows Program — The Anthropic Institute Fellows (Economics & Policy) This is a research fellowship program focused on empirical projects related to AI's economic and societal impacts, with the goal of producing public outputs like research papers. Fellows will use external infrastructure and work with mentors to explore areas such as AI's economic effects, labor markets, and AI-enabled cyber/bio capabilities. | Data | 7 |
| Software Engineer, Research Data Platform Software Engineer to build and operate data pipelines and tooling for AI researchers managing data from training runs, exploring datasets, and analyzing experiments. Focus on data products supporting the research workflow. | Data | 7 |
| Data Engineer, Safeguards Data Engineer for the Safeguards team, responsible for building data pipelines, warehousing solutions, and analytical tooling to support AI safety and trust efforts. The role focuses on data infrastructure for monitoring models, preventing misuse, and ensuring user well-being. | Data | 7 |
| Transformative AI Research Economist, Economic Research This role focuses on building macroeconomic models of transformative AI and developing scenario-based forecasting tools. It grounds projections in microeconomic data from the Anthropic Economic Index, analyzing millions of real-world AI interactions to understand AI's impact on labor markets, productivity, and economic transformation. The role also involves contributing to AI-powered research tools for economics. | Data | 7 |
| Research Economist, Economic Research Research Economist role focused on measuring and understanding the economic impact of AI systems, developing methodologies for the Anthropic Economic Index, and using frontier econometrics and machine learning methods. The role involves analyzing AI interactions, labor market impacts, and productivity, and translating insights into policy and product recommendations. | Data | 7 |
| Data Operations Manager This role focuses on building and scaling data operations for AI research teams, managing the entire data pipeline from requirements to production. It involves partnering with researchers, managing vendors, and ensuring high-quality training data for frontier AI capabilities like RLHF, safety, tool use, and agentic workflows. The role requires operational excellence, technical depth in understanding training data, and strong project management skills. | DataPost-train | 7 |
| Software Engineer, Human Data Interface Software Engineer role focused on building and architecting data collection pipelines and interfaces for human data vendors and crowdworkers to improve AI models. This involves full-stack development, user experience design for data collectors, and collaboration with researchers and data operations teams. | Data | 5 |
| Research Engineer, Economic Research Research Engineer on the Economic Research team responsible for designing, building, and maintaining critical infrastructure for AI's economic impact research. This involves processing large-scale Claude usage logs, expanding privacy-preserving tools, and developing novel data systems that leverage language models, ensuring data reliability, integrity, and privacy compliance. | Data | 5 |
| Engineering Manager, Human Data Interfaces Engineering Manager for the Human Data Interfaces team, responsible for building systems to collect data that improves AI models. This involves developing novel interfaces, tooling, and infrastructure for data vendors and researchers, managing a team of engineers, and collaborating with research teams to ensure high-quality data collection at scale. | Data | 5 |
| Data Engineer, Economic Research Data Engineer on the Economic Research team responsible for building and maintaining data pipelines for AI's economic impact research. This involves processing large-scale usage logs, expanding privacy-preserving tools, designing novel data systems leveraging language models, and ensuring data reliability and privacy compliance. The role collaborates with various teams to support economic analysis and shape the data foundations roadmap. | Data | 5 |
| Economist, Policy This role focuses on researching and measuring the economic effects of AI, developing the Anthropic Economic Index using novel data sources and privacy-preserving tools, and applying frontier methods in econometrics and machine learning. The goal is to understand AI's impact on labor markets, productivity, and economic transformation, influencing policy and product decisions. | Data | 5 |
| Software Engineer, Data Ingestion Software Engineer to join the Data Acquisition team, which owns the problem of acquiring all of the available data on the internet through a large scale web crawler, and through data partnerships. The role involves developing and maintaining internet-scale web crawlers, building data ingestion pipelines, and improving system observability. This is crucial for producing the best pre-trained models. | Data | 5 |