Director, GTM Engineering

The role

The Director, GTM Engineering will own the systems, data, automation, and technical infrastructure powering the go-to-market organization. This role translates business problems into scalable systems, workflows, and AI-powered solutions across the commercial lifecycle.

What you will do

• 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.
• Establish engineering standards for GTM systems and automation.
• Build AI-native workflows and internal tools to reduce manual work.
• Design automation with a simple, auditable, and secure-first approach.
• Build systems and data foundations connecting the commercial lifecycle.
• Partner with Head of Data Intelligence to build a shared data foundation.
• Own technical infrastructure behind forecasting and GTM execution.
• Lead GTM partnership on usage, metering, and billing.
• Lead the GTM Engineering function as a player-coach.

Required qualifications

• Experience building and leading GTM Engineering, RevOps, Sales Ops, Business Systems, or a similar technical GTM function.
• Professional software engineering experience with ability to write, review, debug, and maintain production-quality code independent of AI-assisted development tools.
• Experience in a usage-based or consumption-based business, especially metering and billing infrastructure.
• 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 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.

Nice to have

• Experience with Salesforce, CPQ/billing platforms, SQL, and GTM data pipelines.
• Experience with AI-assisted development tools such as Claude Code, Cursor, to accelerate professional software engineering workflows, alongside automation platforms such as n8n, Workato, or Retool.
• Experience scaling GTM systems through rapid growth or multi-product expansion.

About the company

Deepgram is a research company that productizes as fast as possible, providing speech models and real-time infrastructure for AI systems. Their Voice Agent Platform includes speech-to-text, text-to-speech and speech-to-speech via cloud APIs or self-hosted deployments.