Anthropic· AI Research & Engineering· San Francisco, CA
Research Engineer, AI Observability
Classified Tasks (12)
Automate 0%Augment 83%Human-Only 17%
Augment (10)
AI assists, human decides
Design and build systems that enable AI to analyze large, unstructured datasets and produce structured, trustworthy insights
technical
Design and implement AI-based monitoring systems for AI training and deployment
technical
Scale up existing applications and build new applications from zero to one
technical
Implement and maintain full-stack components, from core analysis frameworks through user-facing apps and interfaces
technical
Extend and improve core frameworks for processing large volumes of unstructured text
technical
Develop agentic integrations that enable AI systems to autonomously investigate and act on analytical findings
technical
Build internal tools with attention to UX, reliability, and documentation
technical
Use LLMs (e.g., Claude) to analyze datasets, surface unexpected patterns, and summarize findings
analytical
Implement mechanisms to maintain meaningful human oversight over massive datasets
operational
Create tooling to surface unexpected patterns to support enforcement, threat intelligence investigations, and model audits
analytical
Human-Only (2)
Requires human judgment
Partner with researchers and safety teams to gather analytical requirements and develop solutions
communication
Contribute to the team's strategic direction by helping decide what to build, what to partner on, and where to invest
leadership
Job description
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team As AI training and deployments scale, the volume of data we need to monitor and understand is exploding. Our team uses Claude itself to make sense of this data. We own an integrated set of tools enabling Anthropic to ask open-ended questions, surface unexpected patterns, and maintain meaningful human oversight over massive datasets. Our tools are widely adopted internally — powering ongoing enforcement , threat intelligence investigations , model audits , and more — and we’re looking for experienced engineers and researchers to both scale up existing applications and go zero-to-one on new ones. About the Role As a Research Engineer on our team, you'll design and build systems that let AI analyze large, unstructured datasets — think tens or hundreds of thousands of conversations or documents — and produce structured, trustworthy insights. You'll work across the full stack, from core analysis frameworks through user-facing apps and interfaces. This is a high-leverage role. The tools you build will be used by dozens of researchers and investigators, and directly shape our ability to measure and mitigate both misuse and misalignment. Responsibilities: Design and implement AI-based monitoring systems for AI training and deployment Extend and improve core frameworks for processing large volumes of unstructured text Partner with researchers and safety teams across Anthropic to understand their analytical needs and build solutions Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings Contribute to the strategic direction of the team, including decisions about what to build, what to partner on, and where to invest You May Be a Good Fit If You: Have 5+ years of software engineering experience, with meaningful exposure to ML systems Are excited about the problem of scaling human oversight of AI systems Are familiar with LLM application development and evaluation Enjoy building tools that other people use — you care about UX, reliability, and documentation Thrive in collaborative, cross-functional environments Strong Candidates May Also Have: Experience with productioniz