Director, GTM Engineering

Own the GTM technology ecosystem across CRM, CPQ, forecasting tooling, data infrastructure, integrations, automation, and internal tooling.

Serve as the technical product leader for GTM systems and Engineering’s primary GTM counterpart, turning business problems into clear requirements, roadmap priorities, and scalable solutions.

Establish engineering standards for GTM systems and automation, including security, governance, testing, observability, access controls, documentation, and safe production deployment.

Build AI-native workflows and internal tools that reduce manual work and improve pipeline management, forecasting, deal execution, renewals, reporting, and decision-making.

Design automation with a simple, auditable, and secure-first approach, breaking workflows into discrete steps and deliberately determining where deterministic automation, AI, or human judgment is appropriate.

Build the systems and data foundation that connects the commercial lifecycle, creating a reliable operating view across pipeline, bookings, contracts, product usage, customer activity, renewals, and expansion.

Partner closely with Head of Data Intelligence to build a shared, well-governed data foundation for GTM, including consistent data models, metadata, definitions, and trusted sources that support both human and AI-driven decision-making.

Own the technical infrastructure behind forecasting and GTM execution, including CRM workflows, data quality, reporting, routing, and the systems used to operationalize approved territory, quota, commission, and capacity plans.

Lead GTM partnership on usage, metering, and billing, helping define requirements, evaluate build-vs-buy decisions, and implement systems connecting product usage, pricing, contracts, billing, and revenue.

Lead the GTM Engineering function as a player-coach, developing a small team while staying close to the work and using automation before defaulting to additional headcount.

Experience building and leading GTM Engineering, RevOps, Sales Ops, Business Systems, or a similar technical GTM function.

Professional software engineering experience with demonstrated ability to write, review, debug, and maintain production-quality code independent of AI-assisted development tools.

A track record of personally designing, coding, testing, and shipping production systems, integrations, automations, agents or internal tools.

Strong understanding of software architecture, APIs, security, governance, testing, observability, access controls, and production engineering practices.

Deep hands-on experience with CRM, CPQ, APIs, integrations, workflow automation, and commercial data.

Experience building AI-powered workflows that replace or materially reduce manual work.

Strong product instincts and the ability to turn ambiguous business problems into buildable solutions.

Technical credibility with Product and Engineering and strong communication with GTM leaders.

Experience partnering with Data or Analytics Engineering teams on data modeling, governance, metadata, and shared data infrastructure.

Strong understanding of pipeline, forecasting, quote-to-cash, and customer lifecycle data.

Comfortable operating as a hands-on player-coach with a small team.