San Francisco, CA
Remote
Senior
Full Time
💰$ 180,000 - $ 240,000
remoteAI-first mindsetvoice AIconversational designstaff level
Requirements
- •Deep experience designing conversational behavior for LLM-based voice agents or assistants, not only scripted IVR flows
- •Real fluency with the speech pipeline, from ASR through LLM to TTS, and a working understanding of where design decisions actually live inside it
- •A track record designing turn-taking, interruption, repair, and confirmation patterns that shipped and held up in production
- •Evidence of building quality measurement into the practice: evals, transcript review, benchmarks, or a structured failure-analysis loop
- •Exceptional writing craft, including sample dialogs, design guidance, and documentation that others can build against
- •Experience influencing engineering and ML partners on behavior they own, without authority over them
- •Experience designing for developers or technical users, including APIs, SDKs, and documentation surfaces
- •A working AI practice, with a point of view on where these tools help and where they mislead
What You'll Do
- •Define the persona and voice system for Deepgram voice agents, and keep it coherent across experiences and use cases
- •Design turn-taking, barge-in, and end-of-turn behavior with ML and Engineering, tuning responsiveness against the risk of interrupting the user, per use case
- •Design conversational repair, no-match and no-input handling, and confirmation strategy, including guardrails that require confirmation before high-stakes actions
- •Own latency-aware pacing and perceived responsiveness: brevity, backchanneling, hold and filler speech, all against real-time budgets
- •Establish conversational-quality evals and a transcript review practice that turns production failures into a repeatable design loop
- •Build the reference agent experiences and developer-facing design guidance that demonstrate best-practice conversation on the Voice Agent API
- •Partner with ML and Research on ASR and TTS behavior, and on the quality criteria that define a good conversation
- •Set the conversation-design principles, review standards, and shared vocabulary the broader team adopts
Nice to Have
- •Time on a named assistant or a production voice agent platform
- •Practice with Wizard of Oz testing and sample dialog methods
- •Hands-on work with eval tooling for LLM or voice quality
- •Experience in high-stakes or regulated conversation domains where confirmation and recovery carry real cost
- •Multilingual or cross-locale conversation design experience
- •Background in high-growth B2B companies with both self-serve and enterprise motions
About Deepgram
Deepgram specializes in providing AI-powered speech-to-text technology that offers audio intelligence, text-to-speech, and voice agent API.
San Francisco, CA
100 - 250
AI & Machine Learning