Head of GTM Engineering

What You'll Own

• Revenue data layer. CRM as the single source of truth, a warehouse that joins pipeline, product usage,
  onchain activity and billing at the account level. Everything below sits on this.
• Signal-based pipeline engine. Outbound triggered by real intent: onchain activity, contract deployments,
  funding events, hiring, product usage. Enrichment, scoring, routing and sequencing, built so reps start their
  day with qualified work, not a blank list.
• Deal intelligence. Call transcripts and email automatically update the CRM, surface risk, and prompt next
  steps. Reps sell; the system does the data entry.
• Forward-deployed engineering on strategic deals. For large enterprise evaluations and RFPs, you
  build the integration prototype, sandbox or custom demo that wins the technical bake-off. You are in the
  room for the hard conversations.
• Internal copilots. Account research, call prep, proposal drafting and objection handling, trained on our
  own win/loss history and customer language.
• Forecasting. A forecast built from pipeline signals and historical conversion, reviewed weekly with the
  CRO. Forecast accuracy is one of your metrics.
• Product feedback loop. Structured objections, feature gaps and lost-deal reasons from sales data,
  delivered to product monthly. Sales becomes a research input, not a complaint channel.

Why this matters beyond sales

You will treat product, customer success and finance as internal customers from day one. The same data
layer powers usage-based billing, churn signals and product prioritisation. You present to the whole
company every quarter, and your backlog is visible to everyone.

What success looks like:

First 30 days: Audit of the current stack and data. Revenue data layer designed and the CRM cleaned
to a defined standard. Backlog agreed with the CRO and ranked by impact.

First 60 days: Signal-based outbound engine live for one segment. Transcript-to-CRM automation in
production. Reps measurably spending more time selling.

First 90 days: Forecast model in weekly use. First strategic deal where your prototype or demo was
decisive. Monthly product feedback loop running.

Ongoing: Rep selling time, pipeline created from signals, cycle time, forecast accuracy, CRM
completeness. Not number of automations shipped.

How we expect you to work:

•  Own outcomes, not tools. You are measured on what changed for the business, not on what you built.
•  Build on real workflows. Nothing gets automated until a rep is already doing it by hand and it is worth
  their time. No cathedrals.
• Ship weekly, ride along monthly. You sit in on calls and deals regularly. Distance from the field is how
  this role fails.
• Stay in the engineering culture. You use the company's stack, review practices and security
  standards. No shadow infrastructure.
• Default to open. Your roadmap, metrics and decisions are visible to the whole company

What are we looking for:

• A strong engineer who is comfortable owning production systems end to end: data pipelines, APIs,
  LLM-based automation, and the occasional front end.
• Direct experience with modern GTM tooling (CRM APIs, enrichment and sequencing platforms, call
  intelligence, warehouse-native analytics) or the ability to learn it in weeks.
• Fluency with LLMs in production: prompting, evaluation, retrieval, agents, and the judgement to know
  when a simple rule beats a model.
• Enough commercial sense to sit in a customer meeting and know what will move the deal.
• Familiarity with crypto and onchain data, or deep curiosity and a fast learning curve.
• You have operated in a high-intensity, high-ownership environment and you liked it.