We’re hiring a GTM Engineer to build and run the Data, Systems & AI Engineering layer underneath DataSnipper’s GTM and Business Operations stack. This is the build function: if RevOps decides what the ICP is, who owns which territory, and what counts as a qualified opportunity, this team turns those decisions into the systems that actually run them.
That’s a bigger remit than any one tool. You’ll own the CRM data architecture, build the enrichment and signal infrastructure that feeds it, run the integrations and governance holding the wider stack together (Clay, Snowflake, Gong, and more), and build the automations and AI agents that turn all of it into something Marketing, Sales, CS, and BD run on every day. You decide how the whole engine is put together, working across every function rather than waiting inside one for requests.
Where the function stands today
We are building this function from scratch, and therefore you will have the opportunity to lay out the foundations of what a world class AI GTM Engineering team can look like in a fast paced AI company. We are looking for a team that can take and build upon the existing state- Marketing has built real foundation where enrichment runs steadily, AI nurturing agents are live and lifting reply rates, intent signals flow in from across the funnel, and HubSpot is trusted as the data model of record for accounts, contacts, deals, and lifecycle stages.
This team will be building the next next frontier: own integrations and vendor tooling (Gong, Snowflake, Clay, Default AI, Common Room, dialers) end to end instead of managing them reactively, and turn data governance - who can touch shared CRM objects, what change control looks like - from a principle into enforced practice. Beyond that, there’s a funnel zone each for Sales, CS, and BD still waiting to be built out, on top of the intelligence Marketing already relies on.
We need operators who are instinctively drawn to turning manual process into clean systems, and ungoverned data into governed infrastructure. People who’ve spent their growth, marketing, sales, or RevOps careers quietly building automations and tightening the infrastructure underneath their own work, and are ready to do both full-time inside a function that already has shape and runway.