Own the TTS category narrative. Define what "TTS for voice agents" means in a way that plays to Deepgram's strengths and makes general-purpose providers look like the wrong tool for the job.
Build and execute GTM strategy across developer adoption, pipeline influence, and account expansion. TTS doesn't always sell alone; know how it fits into voice agent and speech-to-text (STT) deals and make sure it shows up at the right moments.
Lead product launches for TTS releases: new voices, model improvements, latency advances, deployment options. Clear messaging, sharp launch plans, tight cross-functional execution.
Own competitive positioning. Battlecards, objection-handling guides, and displacement plays against ElevenLabs, OpenAI, Amazon Polly, PlayHT, and others. Know where we win, where we lose, and why.
Enable sales and build proof points. Collateral, customer stories, and benchmarks that win TTS deals and surface TTS opportunities in broader conversations.
Collaborate with Product on market and competitive intelligence: what voice agent builders need, what competitors are doing, where the market is going.
Drive developer-facing content and awareness with Developer Relations: tutorials, documentation messaging, 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.
Requirements
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.