AI GTM Engineer

The core responsibilities for the job include the following:

GTM systems and automation:

• Design and build the workflows that connect enrichment, qualification, routing, and outreach into one system that runs at scale.

• Replace manual, repetitive GTM processes with reliable automation.

• Build, run, and own automated campaign pipelines end to end.

• Establish guardrails and monitoring so automated workflows stay accurate as volume grows.

AI agents and tooling:

• Build and configure AI agents for prospecting, enrichment, and personalization.

• Build internal tools so sales and marketing can self-serve on the systems you create.

• Bring AI into the GTM motion in a way that strengthens human judgment rather than replacing it.

Pipeline data and measurement:

• Own and maintain the GTM measurement layer: keep pipeline and funnel data accurate, current, and trustworthy.

• Instrument the funnel end to end and build reporting that connects activity to pipeline and revenue.

Cross-functional partnership:

• Work directly with sales, marketing, and leadership to turn GTM strategy into running systems.

• Translate what the commercial team needs into technical infrastructure they can rely on.

Requirements:

• 2+ years of direct, hands-on experience as a GTM engineer, building and running go-to-market systems.

• Hands-on command of a modern GTM stack: Clay, ZoomInfo, Sales Navigator, Smartlead, HubSpot, or similar tools.

• Full-stack development experience, especially with FastAPI, Next.js, and Node.js .

• API fluency (REST) and the ability to automate against the tools in the GTM stack.

• SQL and data-modeling skills for funnel and pipeline work.

• Strong problem-solving instinct: thinks through edge cases, handles errors gracefully, and builds systems that are maintainable, not brittle.

• Comfortable operating independently and taking full ownership in a fast-moving, ambiguous environment.

• Ideal profile: Someone who bridges the commercial and the technical, the kind of operator who can read a data schema and write the code to work against it in the same afternoon.