Staff Engineer - AI Productivity

About Hightouch

Hightouch is the modern AI platform for marketing and growth teams. Our AI agents reimagine marketing workflows, allowing marketers to create content, plan campaigns, and execute strategies with transformational velocity and performance.

Hightouch is a rare company built on the intersection of two fundamental technological shifts: advances in LLMs and agentic AI, and the rapid adoption of cloud data warehouses like Snowflake and Databricks. Building on these tailwinds, we have become a leader in AI marketing and partner with industry leaders such as Domino’s, Chime, Spotify, Ramp, Whoop, Grammarly, and over 1000 others.

Our team focuses on making a meaningful impact for our customers. We approach challenges with first‑principles thinking, move quickly and efficiently, and treat each other with compassion and kindness. We look for team members who are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals.

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.

• 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 Circle
  
  CI, 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.

This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000 - $320,000 USD per year, which is location independent in accordance with our remote‑first policy. We also offer meaningful equity compensation in the form of ISO options, and offer early exercise and a 10‑year post‑termination exercise window.

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.

• 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…