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Role & Impact:
- Own conversational behavior for Deepgram voice agents, defining persona, turn-taking, repair, and pacing.
- Work directly with ML and Engineering on endpointing, barge-in, and latency budgets to make behaviors real.
- Build evals, transcript review practices, and developer design guidance to scale conversational quality.
What You’ll Do:
- Define persona and voice system, design interruption and confirmation patterns, and own perceived responsiveness against latency budgets.
- Establish quality measurement through evals and structured failure analysis.
- Partner with ML and Research on ASR/TTS criteria and set design principles adopted across the team.
Who You Are:
- Deep experience designing conversational behavior for LLM-based voice agents, not only scripted flows.
- Fluent with speech pipeline and a track record shipping turn-taking and repair patterns.
- Exceptional writing and ability to influence engineering partners without authority.
Deepgram
Deepgram is the leading platform for the Voice AI economy, providing real-time APIs for speech-to-text and text-to-speech, enabling organizations to build production-grade voice agents. Backed by a recent Series C and processed over 50,000 years of audio, Deepgram is a growth-stage company with an AI-first culture where innovation and rapid adaptation are key.