Director, GTM Engineering

Location: United States Company Overview Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. Company Operating Rhythm At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. 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. 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 in a usage-based or consumption-based business, especially metering and billing infrastructure. 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. 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