Company Overview
Deepgram is bringing the world’s most natural interface, voice, to the technology we use every day. Our speech models and real-time infrastructure power AI systems that keep up with the way people actually speak. More than 5,000 organizations run conversational voice AI on Deepgram in production, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Cresta, Granola, and Jack in the Box.
The Deepgram Voice Agent Platform brings together speech-to-text, text-to-speech and speech-to-speech, with voice-native foundation models available through cloud APIs or self-hosted and on-premises deployments. Built for accuracy, low latency and cost efficiency, Deepgram makes high-quality voice experiences practical to build and run at scale. More than 650,000 developers have used Deepgram to process more than 200,000 years of audio. Every day, more of the world’s conversations with AI run on our models.
Operating Principles:
Deepgram is a research company that productizes as fast as possible. Four Operating Principles shape how we think, decide, and work together:
Compress before you communicate. You think it through first, then lead with the bottom line.
Resist entropy. You question what already exists before adding more process or tools.
Solve the category. You fix recurring problems at the source, not one case at a time.
Work at the frontier. You go after problems no one has solved yet.
We look for people who already work this way, and these principles shape how we grow and evaluate our team.
AI-First by Default
We build AI that millions of people talk to, and we run the company the same way. AI is how we centralize work here, and is core to how we operate.
That means more than using the tools. We expect you to:
Build, not just use. Design your own workflows and agents, and use AI to remove whole categories of work instead of doing the same work faster.
Own the output. AI can speed up the work. It doesn’t make anyone less accountable for it. You understand, verify, and stand behind everything you share, including what an agent produces for you.
Spend the time you get back at the frontier. The capacity AI creates goes toward problems no one has solved yet.
Keep pace. Models and tools change every month, and so will your work. You adopt what’s new quickly and drop what no longer earns its place.
We judge AI by what it helps you deliver and whether you stand behind the result, not by how often you use it. In interviews, expect to walk us through a workflow you built and where you drew the line between AI and your own judgment.
Deepgram is hiring a Director, GTM Engineering to own the systems, data, automation, and technical infrastructure that power our go-to-market organization.
This role sits at the intersection of GTM, Product, Engineering, and Finance and supports the full commercial lifecycle — from pre-sales and pipeline through contracting, usage, renewal, and expansion. You’ll own our GTM technology ecosystem as an internal product, translating business problems into scalable systems, workflows, data, and AI-powered solutions.
This is a builder-leader role. We need someone who can set the architecture and roadmap while staying close enough to the work to diagnose problems, prototype solutions, write requirements, interrogate data, and ship. You’ll start with a small team and build leverage through better systems and automation before defaulting to additional headcount.
What You’ll 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 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.
What We’re Looking For
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.
Experience in a usage-based or consumption-based business, especially metering and billing infrastructure.
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.
Would Be Great if You Had
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.
Notice: We’re aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com email address. If you’ve received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
