Staff Engineer, AI Productivity

Responsibilities

• Own the agentic development environment: Ensure agents can operate in independent cloud-based development environments, execute full test suites, examine build results visually
• Build tooling integrations: Build MCP server integrations that connect agents to systems needed to build and debug software (CircleCI, Slack, Datadog, Github, etc.)
• Documentation and context: Own repo-wide agents.md file and work with teams to ensure library of agent guidance and skills is continually pushing the bar; ensure conventions and package structures are exposed in ways agents can effectively use
• Enablement: Work with engineers to understand where agents are struggling and address root causes such as better docs, tooling access; develop tooling for non-engineers to make simple visual updates to the application
• Serve as a "PM" for internal AI agents: Stay abreast of state-of-the-art AI productivity trends and drive improvements across the organization

Requirements

• Strong software engineering fundamentals—you can dive into complex backend code and understand it quickly
• Deep hands-on experience with AI coding agents (Claude Code, Cursor, Copilot, Devin, or similar)
• Experience writing effective agent documentation, custom instructions, or context files that meaningfully improved agent output
• Track record of building developer tools or infrastructure that other engineers actually use
• Comfortable working across the stack: CI/CD, cloud infrastructure, internal tooling, and application code

Nice to Have

• Experience building or contributing to MCP servers or similar agent-tooling integrations
• Background in developer productivity, platform engineering, or developer experience roles
• Experience with TypeScript/JavaScript monorepos, Go, GraphQL
• Experience setting up sandboxed or containerized development environments at scale