Staff Engineer, AI Productivity

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Engineer, AI Productivity based in United States. This is a hands-on technical leadership role focused on transforming how engineering teams build software with AI. You will own the infrastructure, tooling, integrations, and documentation that enable AI coding agents to work effectively across a large codebase. The role spans cloud-based development environments, agent tooling, CI/CD, internal systems, documentation, and application development. You will help engineers overcome AI productivity barriers by identifying root causes and building practical solutions that improve developer workflows. You will also shape the organization’s approach to emerging AI development practices, staying close to the latest advances and turning them into measurable improvements. With significant autonomy and ownership, you will combine deep engineering expertise with cross-team influence and technical leadership. This is an opportunity to play a defining role in building the next generation of AI-assisted software development.

Own and evolve agentic development environments that allow AI agents to operate independently in cloud-based, sandboxed, or containerized environments and execute comprehensive test suites. Build and maintain integrations that give AI agents access to essential engineering systems and context, including CI/CD, source control, communication, observability, and monitoring platforms. Develop MCP servers and similar agent-tooling integrations that enable agents to build, debug, test, and operate software more effectively. Own and continuously improve repo-wide AI documentation, agent instructions, skills, context files, conventions, and package guidance so agents can navigate and contribute to the codebase effectively. Work directly with engineers to identify where AI agents struggle and address underlying issues through improved documentation, tooling, context, infrastructure, and workflows. Develop tools and workflows that allow non-engineering teams to make simple visual or application updates with AI assistance. Act as the internal product owner for AI agent capabilities, identifying emerging technologies and industry practices and driving their adoption across engineering. Lead cross-functional initiatives that raise the effectiveness and consistency of AI-assisted development across teams. Maintain a strong hands-on contribution to engineering projects while providing technical leadership and helping establish best practices for AI-powered development. Requirements Strong software engineering fundamentals with the ability to quickly understand and work within complex backend codebases. Deep hands-on experience using AI coding agents such as Claude Code, Cursor, GitHub Copilot, Devin, or comparable tools. Demonstrated experience creating effective agent documentation, custom instructions, context files, or similar resources that measurably improve AI-generated output. Proven track record of building developer tools, infrastructure, or internal platforms that are actively adopted and used by other engineers. Comfortable working across the technology stack, including CI/CD systems, cloud infrastructure, internal tooling, and application code. Strong problem-solving skills and a practical approach to identifying technical bottlenecks and creating solutions that deliver measurable value. High ownership and autonomy, with the ability to operate effectively in a fast-paced startup environment. Strong communication and cross-functional collaboration skills, with the ability to influence engineering teams and drive change without relying solely on formal authority. Experience building or contributing to MCP servers or other agent-tooling integrations is a strong plus. Background in developer productivity, platform engineering, developer experience, or related engineering disciplines is advantageous. Experience with TypeScript/JavaScript monorepos, Go, and GraphQL is a plus. Experience designing sandboxed or containerized development environments at scale is desirable. Intellectual curiosity, adaptability, and a strong interest in emerging AI development technologies are essential. Benefits Competitive annual salary range of USD $180,000–$400,000 , with compensation designed to be location-independent under a remote-first model. Meaningful equity compensation. Fully remote work environment across North America. High degree of autonomy and ownership in a high-impact technical role. Opportunity to shape AI-assisted engineering practices and influence how teams build software. Exposure to rapidly evolving AI technologies and the opportunity to work with cutting-edge coding agents and agent infrastructure. Strong opportunities for technical leadership, cross-functional influence, and professional growth. A fast-paced, intellectually curious environment focused on measurable impact rather than tenure.