Staff Engineer, AI Productivity

New

JobgetherAI developer tooling

Listing location: USFull-TimeStaff

SalaryUSD $180,000–$400,000

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Job Details

Have strong software engineering fundamentals and the ability to quickly understand and work within complex backend codebases.
Have deep hands-on experience using AI coding agents such as Claude Code, Cursor, GitHub Copilot, or Devin, or comparable tools.
Have demonstrated experience creating agent documentation, custom instructions, context files, or similar resources that improve AI-generated output.
Have a track record of building developer tools, infrastructure, or internal platforms actively adopted by other engineers.
Be comfortable working across CI/CD systems, cloud infrastructure, internal tooling, and application code.
Bring a practical approach to identifying technical bottlenecks and developing solutions that deliver measurable value.
Be able to operate with high ownership and autonomy in a fast-paced startup environment.
Have strong communication and cross-functional collaboration skills, and be able to influence engineering teams and drive change.
Experience with MCP servers or other agent-tooling integrations is a plus.
Background in developer productivity, platform engineering, developer experience, or related engineering disciplines is advantageous.
Experience with TypeScript/JavaScript monorepos, Go, or GraphQL is a plus.
Experience designing sandboxed or containerized development environments at scale is desirable.

Own and evolve cloud-based, sandboxed, or containerized development environments where AI agents can operate independently and run comprehensive test suites.
Build and maintain integrations connecting AI agents with CI/CD, source control, communication, observability, and monitoring platforms.
Develop MCP servers and other agent-tooling integrations that help agents build, debug, test, and operate software.
Improve repo-wide AI documentation, agent instructions, skills, context files, conventions, and package guidance.
Work with engineers to identify agent limitations and address underlying issues in documentation, tooling, context, infrastructure, and workflows.
Develop AI-assisted tools and workflows for non-engineering teams to make simple visual or application updates.
Identify emerging AI technologies and industry practices and drive their adoption across engineering.
Lead cross-functional initiatives to improve the effectiveness and consistency of AI-assisted development.
Contribute hands-on to engineering projects while providing technical leadership and establishing best practices for AI-powered development.

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