Head of AI Enablement Engineering

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 200000 developers and 1300+ 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 50000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.

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's ambition is to build a generational company with a small exceptional team — which only works if every engineer and every function operates with serious AI leverage. We're looking for a Head of AI Enablement Engineering to own that mission end to end: making Deepgram one of the most AI-native companies in the world in practice and not just in principle.

This is a build-first leadership role not a steward or training role. You'll personally evaluate tools build the agents and workflows that show what great looks like and set the standards that the rest of the company adopts. You'll turn our AI-native strategy into shipped capability — reusable agents and skills MCP integrations paved-road workflows and the enablement hub and patterns that let any team go from idea to working tool fast and safely. You'll partner closely with Engineering Platform/Internal Tools People Ops and functional leaders across the company and you'll be measured on real outcomes: adoption productivity and the quality of what people build.

You'll lead largely through building and influence with the runway to grow a small team and a network of champions as the function scales. It's a high-visibility seat with executive sponsorship and a mandate to set direction where there is no established playbook.

• Own and drive AI enablement engineering across Deepgram — the strategy the standards and the hands-on building that make AI leverage real in every function.

• Personally evaluate prototype with and make the calls on the AI tools agents models and orchestration layers Deepgram adopts; avoid tool sprawl and make pragmatic build-vs-buy decisions.

• Build the reference implementations: reusable agents and skills MCP servers paved-road workflows prompt and pattern libraries and the enablement hub where the best internally-built tools are surfaced and elevated.

• Set and run the company-wide AI adoption strategy — the metrics milestones and reporting cadence leadership uses to track progress framed around measurable productivity and quality not activity.

• Partner with Platform/Internal Tools Security and Data to define guardrails that are embedded into platforms rather than enforced through gates — safe-use patterns access and data handling that make adoption easier not harder.

• Build and lead a distributed champions network embedded in teams and grow a small central team over time as impact scales.

• Partner with People Ops on AI-native onboarding and fluency so new and existing teammates do real reps inside the tools and leave the system better than they found it.

• Stay ahead of a fast-moving landscape and translate emerging AI capabilities into pragmatic Deepgram-ready practice.

• Want to define how an entire company works with AI — and you'd rather build the proof than write the memo.

• Are energized by ambiguity and a blank page and you set direction where there's no playbook yet.

• Are hands-on and current: you build agents and workflows yourself and can sit across from senior engineers as a peer on day one.

• Care about real outcomes — adoption time saved quality — not vanity metrics or shelf-ware.

• Like operating across an org bringing skeptical teams along through demonstrated value rather than mandate.

• Believe a small AI-leveraged team can outbuild a much larger one.

• A strong engineering background with the hands-on ability to build production-quality agents tools and automations yourself.

• Deep current fluency with the modern AI tooling landscape — coding agents LLM application patterns prompting retrieval MCP/agent tooling and orchestration.

• A track record of driving technology adoption and changing how people work at scale in environments that didn't start out asking for it.

• The ability to operate across business and technical functions and influence without direct authority including credibility with senior engineering leaders.

• Strong product and platform instincts — you treat enablement as a product with users adoption and a roadmap.

• Excellent communication — you can demo document evangelize and report outcomes to executives in plain language.

• Comfort defining safe-use guardrails and data-handling practices in partnership with Security and Platform.

• Experience standing up an AI enablement developer productivity or engineering effectiveness function from scratch.

• Background building internal platforms or developer-facing tooling that engineers actually adopted.

• Experience leading a small team and/or a distributed champions/center-of-excellence model.

• Familiarity with enterprise AI search and knowledge tooling (e.g. Glean Notion AI) and agent orchestration frameworks.

• A point of view on measuring developer productivity and AI impact with the nuance that entails.

• Experience in a fast-moving AI-native engineering organization.

What We Do

Deepgram is the leading voice AI platform for developers building speech-to-text (STT) text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy latency and pricing. Customers include software companies building voice products co-sell partners working with large enterprises and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers 3.3x annual usage growth across the past 4 years over 50000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than Deepgram.

Why Work With Us

Our culture like our product is constantly learning and evolving but the heart of our team is enduring. We are a self-motivated positive passionate and competitive group of people. At Deepgram we put an emphasis on being ourselves being curious growing together and being human. We are a unique bunch who celebrate our differences.

Gallery