Want to know if this job is worth applying to?
Remote, Oregon, United States
Remote only
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.
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.
Voice agents are becoming standard infrastructure for customer-facing businesses, and the platform teams build on decides whether they ship something production-grade or something that stalls in a demo. Deepgram Voice Agent is a single, unified API that combines speech-to-text, LLM orchestration, and text-to-speech in real time: the full voice stack, owned end to end. We're looking for a Senior PMM to own our go-to-market motion and make Deepgram the default teams reach for when they move from prototype to production.
This is a market ownership role. You'll define how Deepgram shows up in a crowded, fast-moving category, build the narrative for where an owned, end-to-end runtime fits across how teams build voice agents, drive adoption from developer trial through enterprise deployment, and own product launches as they come. You'll work across Product, Sales, Developer Relations, and Demand Gen to keep the voice agent story consistent, compelling, and closing deals.
We're an AI-native team. We expect AI to be woven into how you work, not something you reach for occasionally.
Own the voice agent category narrative. Define what a production-grade voice agent platform is in a way that plays to Deepgram's strengths: one owned, end-to-end stack with sub-300ms latency, barge-in, and turn-taking.
Build and execute GTM strategy across developer adoption, pipeline influence, and account expansion. Voice agents are where STT, TTS, and LLM orchestration come together; own the full-stack story while knowing how the pieces show up in broader deals.
Lead product launches for Voice Agent releases: new conversational capabilities, latency and quality advances, BYO model support, deployment and compliance options. Clear messaging, sharp launch plans, tight cross-functional execution.
Own positioning across the build spectrum. Understand the different approaches teams take to building voice agents, from DIY frameworks to managed platforms and enterprise suites, and build the battlecards, objection-handling guides, and build-vs-buy narratives that show why the unified-API approach wins for production. Many players here are partners who embed Deepgram as their speech layer.
Enable sales and build proof points. Collateral, customer stories, benchmarks, and TCO narratives that win voice agent deals and stand up to technical and economic scrutiny.
Collaborate with Product on market and competitive intelligence: what voice agent builders need, what the market is shipping, where it's going.
Drive developer-facing content and awareness with Developer Relations: tutorials, documentation messaging, reference architectures, use case content, and SEO tied to how voice agent builders actually search.
Build AI-assisted PMM workflows. Use AI to accelerate research, competitive synthesis, and content production. Build repeatable systems, not one-off prompts. You set the strategy; AI handles the first drafts.
Are energized by owning a market, not just supporting a product. You want to shape how buyers think about the problem.
Understand the voice agent stack well enough to tell a coherent story about why an owned, end-to-end platform beats a stitched-together one, and where the build-vs-buy line falls for different buyers.
Move fluidly between a developer audience and a business buyer without losing either one.
Are comfortable marketing a product with both a technical architecture story and an experiential one, where one buyer is reading API docs and another is judging whether the agent sounds and responds like something they'd put in front of customers.
Default to AI-first: you use AI continuously, have good judgment about when it's wrong, and think in systems rather than one-off prompts.
5+ years of product marketing experience, including at least 2 years on infrastructure, API, or developer-facing products.
Strong messaging skills: you can build a positioning architecture from scratch and know the difference between a message that's technically accurate and one that actually moves people.
A high bar for quality: you notice when copy is off, when a layout doesn't work, when creative doesn't match the brand, and you can give useful feedback on all of it.
Working knowledge of the AI landscape: frontier models, major LLM providers, how the ecosystem fits together. You need to talk about this credibly with technical buyers.
Technical depth: you can engage with engineering and product teams, read API docs, and translate product-level details into market-facing narratives without oversimplifying.
Fluency in both product-led and sales-led growth motions, and how they interact.
Demonstrated AI fluency: concrete examples of AI-assisted workflows you've built, iterated on, and measured, with specific outcomes to back it up.
Experience in the voice AI space and familiarity with how STT, TTS, and LLMs come together in a production voice agent stack, and with the range of ways teams build voice agents, from DIY frameworks to managed platforms.
Hands-on experience with AI-native tools across the stack: agentic coding (Claude Code, Codex) and collaborative work tools (Cowork, etc.).
Experience with technical proof points, model benchmarks, or evaluation frameworks. In voice agents, buying decisions often come down to a live conversation that either feels natural or doesn't.
Comfort operating where the playbook doesn't fully exist yet and you're building it as you go.
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.
