Staff Engineer, AI Productivity

Hightouch; San Francisco (CA); Remote; USD 180,000 - 400,000; Full time

Benefits offered by this job

Equity compensation

Job summary

Hightouch is seeking a Staff AI Productivity Engineer to accelerate how our engineering teams work with AI coding tools. This hands-on role builds infrastructure, tooling, and documentation to make AI agents dramatically more effective across our codebase.

You’ll own end-to-end environments for autonomous agents, integrate MCP server connections to systems like CircleCI, Slack, Datadog, and write clear agent guidance to raise the bar across teams.

Qualifications

• Strong software engineering fundamentals; can read complex backend code 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 improve agent output.
• Track record of building developer tools or infrastructure that engineers actually use.
• Comfortable across the stack: CI/CD, cloud infrastructure, internal tooling, and application code.

Responsibilities

• Own the agentic development environment and ensure agents run in cloud-based dev environments.
• Build MCP server integrations to connect agents with systems like CircleCI, Slack, Datadog, Github, etc.
• Document and maintain repo-wide agents.md and agent guidance used across teams.
• Address root causes by improving docs and tooling; enable non-engineers to make simple UI updates.
• Act as a PM for internal AI agents, staying current with industry productivity trends and driving improvements.

Skills

Software engineering fundamentals

AI coding agents

Agent documentation

Developer tooling

CI/CD experience

Tools

MCP servers

TypeScript

Go

GraphQL

Job description

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 hands-on technical role focused on building infrastructure, tooling, and documentation that makes AI agents dramatically more effective across our codebase.

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 hands-on 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 end-to-end: 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.

You’ll have the hands-on acumen to do a lot of the heavy lifting yourself and the leadership skills to drive cross-team 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 AI-assisted development experience. An exceptional candidate could wear both hats.

Some of the problems we’ll be working on include:

• Own the agentic development environment: Ensure agents can operate in independent cloud-based 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 repo-wide 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 non-engineers to make simple visual updates to our application
• Serve as a “PM” for internal AI agents: Consistently keep us on the leading edge of AI productivity trends by staying abreast of what is state-of-the-art 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 remote-first 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. You’re motivated by high ownership and are comfortable in a fast-paced, startup environment.

Must have

• 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: you'll touch 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 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 don’t ask you to write code to solve technical brainteasers that don’t 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 end-to-end
• AI Skills Interview [60m]: We’ll dive into how you leverage AI and how you’ve 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