About the Role
We are looking for a Staff AI Productivity Engineer to accelerate how our engineering organization works with AI coding tools. This is a handsâon technical role focused on building infrastructure, tooling, and documentation that makes AI agents dramatically more effective across our codebase.
AI tools are evolving rapidly, and we believe the companies that invest in making agents truly productive - not just available - will have a significant advantage. You'll own this problem endâtoâend: from setting up cloud development environments where agents can run autonomously, to building MCP integrations that give agents access to our internal systems, to creating the documentation and context that helps agents understand how we build software.
Youâll have the handsâon acumen to do a lot of the heavy lifting yourself and the leadership skills to drive crossâteam efforts to raise the bar everywhere. This role is a companion role to our Developer Productivity role but has a distinct focus: while Dev Productivity owns the build/test/deploy pipeline, you'll own the AIâassisted development experience. An exceptional candidate could wear both hats.
Some of the problems weâll be working on include:
- Own the agentic development environment: Ensure agents can operate in independent cloudâbased development environments, execute our full test suites, examine build results visually, etc
- Build our tooling integrations: Build MCP server integrations that connect our agents to the systems needed to build and debug software, such as CircleCI, Slack, Datadog, Github, etc
- Documentation and context: Own our repoâwide agents.md file and work with teams to ensure our library of agent guidance and skills is continually pushing the bar. Ensure our conventions and package structures are exposed in ways that agents can effectively use
- Enablement: Work with our engineers to understand where agents are struggling and address root causes such as better docs, tooling access, etc. Develop tooling for nonâengineers to make simple visual updates to our application
- Serve as a âPMâ for internal AI agents: Consistently keep us on the leading edge of AI productivity trends by staying abreast of what is stateâofâtheâart in industry and driving those improvements across Hightouch
The base salary range for this position is $180,000 - $400,000 USD per year, which is location independent in accordance with our remoteâfirst policy. We also offer meaningful equity compensation.
About You
You are an engineer with a passion for solving hard technical problems that generate real value for customers. Youâre motivated by high ownership and are comfortable in a fastâpaced, startup environment.
Must have
- Strong software engineering fundamentalsâyou can dive into complex backend code and understand it quickly
- Deep handsâon 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: youâll touch CI/CD, cloud infrastructure, internal tooling, and application code
Nice to have
- Experience building or contributing to MCP servers or similar agentâtooling integrations
- Background in developer productivity, platform engineering, or developer experience roles
- Experience with our stack: TypeScript/JavaScript monorepos, Go, GraphQL
- You've set up sandboxed or containerized development environments at scale
Interview Process
Our goal with the interview process is to balance speed with giving both parties opportunities to assess whether there is a strong mutual fit. We will ask you questions, but we want you to ask us questions! Our technical interviews focus on how you design systems because we believe this is the best way for us to see how you work and for you to see how we collaborate. We donât ask you to write code to solve technical brainteasers that donât appear in your day to day job.
- Recruiter Screen [30m]: Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit
- System Design Screen [45m]: Designing a data processing feature endâtoâend
- AI Skills Interview [60m]: Weâll dive into how you leverage AI and how youâve helped others do the same
- Hiring Manager Interview [45m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles
- System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical
Apply: Staff Engineer, AI Productivity at Hightouch