Director, GTM Engineering

Deepgram•,

1d•$200,000 - $275,000

About The Position

Deepgram is hiring a Director, GTM Engineering to own the systems, data, automation, and technical infrastructure that power its go-to-market organization. The role sits at the intersection of GTM, Product, Engineering, and Finance, supporting the commercial lifecycle from pre-sales and pipeline through contracting, usage, renewal, and expansion. The Director will own the GTM technology ecosystem as an internal product, translating business problems into scalable systems, workflows, data, and AI-powered solutions. This is a builder-leader and player-coach role. The Director will set architecture and roadmap while remaining hands-on: diagnosing problems, prototyping solutions, writing requirements, interrogating data, and shipping. The role begins with a small team and emphasizes creating leverage through better systems and automation before adding headcount. Deepgram expects an AI-first mindset, active use and experimentation with advanced AI tools, and adaptability as work and priorities evolve rapidly.

Requirements

Experience building and leading GTM Engineering, RevOps, Sales Ops, Business Systems, or a similar technical GTM function.
Professional software engineering experience, with the ability to write, review, debug, and maintain production-quality code independently 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 ability to turn ambiguous business problems into buildable solutions.
Technical credibility with Product and Engineering and strong communication skills 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.
Comfort operating as a hands-on player-coach with a small team.
Comfort adopting new AI models and tools, integrating them into workflows, experimenting, adapting, and learning continuously.

Nice To Haves

Experience in a usage-based or consumption-based business, especially metering and billing infrastructure.
Experience with Salesforce, CPQ or billing platforms, SQL, and GTM data pipelines.
Experience with AI-assisted development tools such as Claude Code or Cursor, alongside automation platforms such as n8n, Workato, or Retool.
Experience scaling GTM systems through rapid growth or multi-product expansion.

Responsibilities

Own the GTM technology ecosystem, including CRM, CPQ, forecasting tools, data infrastructure, integrations, automation, and internal tools.
Serve as the technical product leader for GTM systems and Engineering’s primary GTM counterpart, translating business problems into 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 to reduce manual work and improve pipeline management, forecasting, deal execution, renewals, reporting, and decision-making.
Design automation that is simple, auditable, and secure, determining where deterministic automation, AI, or human judgment is appropriate.
Build systems and data foundations connecting pipeline, bookings, contracts, product usage, customer activity, renewals, and expansion.
Partner with the Head of Data Intelligence on a well-governed GTM data foundation, including consistent data models, metadata, definitions, and trusted sources for human- and AI-driven decisions.
Own technical infrastructure for forecasting and GTM execution, including CRM workflows, data quality, reporting, routing, and systems for operationalizing approved territory, quota, commission, and capacity plans.
Lead GTM partnership on usage, metering, and billing, defining requirements, evaluating build-versus-buy decisions, and implementing systems that connect product usage, pricing, contracts, billing, and revenue.
Lead and develop a small GTM Engineering team as a player-coach, staying close to the work and using automation before defaulting to additional headcount.