About the role

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 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.

What you will be doing

CRM & data architecture

Administer and evolve the HubSpot data model: accounts, contacts, deals, and lifecycle stages.

Implement lead routing, ICP, and territory logic into the CRM per rules RevOps defines - you build it, RevOps owns what it means.

Implement rules of engagement (ROE) - handoff criteria and account rules - into CRM workflows, automation, and Clay infrastructure that execute them reliably.

Enrichment & signals

Build and maintain enrichment via Clay and providers such as ZoomInfo, Apollo, Clearbit, and Starbridge.

Run TAM analysis and intent-data infrastructure, and keep data quality high through continuous enrichment workflows.

Decide which signals matter, how to surface them, and how to route them to the people who should act on them.

Be the mirror and advisor to the business teams through your work

Integrations, tooling & governance

Own GTM tool integrations end to end (Gong, Snowflake, Clay, Default AI, Starbridge, dialers, Common Room, or equivalent) so data flows cleanly with no duplicate or conflicting records.

Apply data governance standards: review automation that touches shared CRM objects, and respect change control on the data model.

Shape vendor and tool decisions - fit, overlap, integration complexity - so we consolidate instead of running five tools for one job.

Automation & AI build

Build and maintain the core Clay & Lemlist infrastructure: account data, enrichment, sequences, templates, and how contacts flow in and out.

Develop account scoring models and standardized Clay functions that Sales and Marketing can use without building their own underlying workflows.

Build agents, automations, and AI-assisted workflows in Claude, Default AI, and connected tooling.

Activate the build across every funnel zone

Marketing (inbound signal → MQL): inbound enrichment and routing, audience activation, intent signal infrastructure. Drive signal-based outbound - detect a buying moment (hiring, funding, leadership change, product usage shift), find the decision-maker, enrich, send.

Sales (SQL → Closed Won → Renewal → Expansion): prospecting automation, account planning tooling, rep efficiency. Build lifecycle expansion plays triggered by product signals so CS and AEs get prompted when an account is ready to expand.

BD (outbound signal → partner + BD pipeline): partner signal workflows, account intelligence, BD-specific outreach and pipeline automation.

CS (Closed Won → Adoption + Health): onboarding automation, health-score workflows, renewal and expansion signal tooling.

Partner with Ops

Work through a request → brief → build → feedback model. Ops people are the interface; they translate field needs into precise briefs you execute against.

Functions consume what you build rather than configuring or building it themselves, and feedback routes back through Ops - keeping your time focused on builds, not ad hoc asks or slides.

What we're looking for

The mindset matters more than the title on your CV.

2-4 years in RevOps, marketing/sales/CS operations, data/CRM administration, or a closely adjacent role. Prior GTM Engineering experience is a plus, not a requirement - the strongest people in this discipline today are crossovers.

AI fluency you actually use. You've been integrating LLMs, automations, and agents into your work for a while. You can talk concretely about what works, what breaks, and what's still a hack.

A builder's mentality. When you hit a wall, you build the thing rather than file a ticket. You pick up Lovable, Bolt, n8n, or whatever new tool surfaces. You've shipped automations that touched real revenue.

Comfort owning infrastructure, not just automations. You own a data model, an integration, or a governance rule as confidently as you own the plumbing - not just what sits on top of it.

A commercial bias. You ask “does this help close a deal?” before “is this elegant?” You measure your work in meetings booked and pipeline influenced.

Cross-functional comfort. You can move between marketing, sales, CS, and engineering languages without losing the room.

Tools you'll work with (willingness to ramp matters more than checklist completeness):

CRM and data architecture: HubSpot

Enrichment and orchestration: Clay, ZoomInfo, Apollo, Clearbit, Starbridge

Integrations: Gong, Snowflake, Default AI, dialers, Common Room

AI tooling: Claude Enterprise (Projects, Skills, and MCP integrations all unlocked), plus ChatGPT, and a flexible stack. Think: n8n, Lovable, Bolt.

Workflow automation: Zapier, HubSpot workflows

Bonus: SQL, Python, or TypeScript. The real signal is willingness to learn by tinkering.