GTM Engineer

GTM Engineer

Location : New York City (hybrid, four days a week in office)

Compensation : $130,000–$175,000 base + bonus

Our client makes research faster without cutting people out of it. Their AI platform runs in-depth customer interviews at scale and turns hours of conversation into findings in days instead of weeks. Unlike a lot of the AI research tools that have shown up lately, it was built on the idea that researchers still belong in the room. Brands you'd recognize use it, the company is growing fast, and it's backed by a top-tier venture firm.

The role

This is the person who builds the machinery behind the sales, marketing, and customer success teams. You'll find the accounts worth calling, automate the work nobody should be doing by hand, and turn the experiments that work into systems that keep working. It used to be called rev ops. It's become more interesting than that.

You'll report to the Head of Sales and take on projects for marketing and customer success too. Most requests will start with "here's what we need, can you help?" The best version of this hire also spots what nobody has thought to ask for yet.

What you'll do

• Own CRM reporting and dashboards for sales and customer success (currently HubSpot)
• Pull together website, intent, event, and market data to find the accounts that are ready to talk
• Build target lists for outbound, and map conference attendees against the ideal customer profile before anyone books a booth
• Build workflows for enrichment, contact sourcing, scoring, and personalized outreach
• Use LLMs, agents, and APIs to automate account research, meeting prep, follow-up, and anything else that eats a rep's afternoon
• Flag expansion opportunities and account health signals so customer success can act early
• Run GTM experiments, measure what moves, and keep improving what works
• Own the integrations and data flows across the stack (currently HubSpot, Clay, and Lemlist), and keep them accurate

What you bring

• 5+ years of experience, with 3+ in GTM engineering, rev ops, growth engineering, solutions engineering, or something close
• Hands-on experience building automation, data, and AI workflows, including LLMs and APIs
• You use AI heavily in your own work already, and you'd rather build a tool than wait for one
• Results you can point to: pipeline created, hours saved, conversion improved
• A real understanding of how B2B pipeline gets built and deals get won
• The ability to explain technical work to non-technical people: what's possible, how long it'll take, and when the 80/20 version is the right call
• Close attention to detail, and the ability to work independently without much oversight
• Comfort in a startup that's still figuring parts of itself out

You don't need a research background. If you've taught yourself most of this, that counts, as long as you can show what you've built.