Research Engineer, AI Observability

Anthropic Anthropic · AI Frontier · San Francisco, CA · AI Research & Engineering

Research Engineer focused on designing and building AI-based monitoring systems to analyze large unstructured datasets, produce structured insights, and develop agentic integrations for investigation and action. The role involves working across the full stack, from core analysis frameworks to user-facing applications, with a direct impact on measuring and mitigating AI misuse and misalignment. This role is critical for scaling human oversight of AI systems.

What you'd actually do

  1. Design and implement AI-based monitoring systems for AI training and deployment
  2. Extend and improve core frameworks for processing large volumes of unstructured text
  3. Partner with researchers and safety teams across Anthropic to understand their analytical needs and build solutions
  4. Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings
  5. Contribute to the strategic direction of the team, including decisions about what to build, what to partner on, and where to invest

Skills

Required

  • Software engineering
  • ML systems
  • LLM application development
  • LLM evaluation
  • building tools
  • UX
  • reliability
  • documentation
  • collaborative, cross-functional environments

Nice to have

  • productionizing internal tools
  • building developer-facing platforms
  • monitoring systems
  • observability systems
  • ambiguity

What the JD emphasized

  • 5+ years of software engineering experience
  • meaningful exposure to ML systems
  • familiar with LLM application development and evaluation
  • building monitoring or observability systems

Other signals

  • design and build systems that let AI analyze large, unstructured datasets
  • produce structured, trustworthy insights
  • work across the full stack, from core analysis frameworks through user-facing apps and interfaces
  • tools you build will be used by dozens of researchers and investigators
  • directly shape our ability to measure and mitigate both misuse and misalignment
  • AI-based monitoring systems for AI training and deployment
  • Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings