Research Engineer, AI Observability

Anthropic•San Francisco, CA

13h•Hybrid

About The Position

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.

Requirements

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 (context engineering, evaluation, orchestration)
Enjoy building tools that other people use — you care about UX, reliability, and documentation
Can context-switch between deep infrastructure work and user-facing product thinking
Thrive in collaborative, cross-functional environments

Nice To Haves

Research experience in AI safety, alignment, or responsible deployment
Practical experience with both data science and engineering, including developing and using large-scale data processing frameworks
Experience with productionizing internal tools or building developer-facing platforms
Background in building monitoring or observability systems
Comfort with ambiguity — our team is small and growing, and you'll help define what we become

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