Remote Staff Conversational Designer — Voice Agents

Deepgram; San Francisco (CA); On-site; USD 170,000 - 240,000; Full time

Job summary

Deepgram is seeking a Staff Conversational Designer to define how our voice agents converse—persona, turn-taking, repair, confirmation, and pacing. You will work directly with ML and Engineering on the tradeoffs that make these behaviors real, including endpointing, barge-in, and latency budgets.

You will build the evals that tell us whether a conversation is actually good, and publish the guidance and reference experiences that show developers how to build natural conversations on the Voice

Qualifications

• 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 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.

Responsibilities

• 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.

Skills

Conversational design

Cross-functional collaboration

Technical writing

Stakeholder influence

Job description

Deepgram is seeking a Staff Conversational Designer to define how our voice agents converse—persona, turn-taking, repair, confirmation, and pacing. You will work directly with ML and Engineering on the tradeoffs that make these behaviors real, including endpointing, barge-in, and latency budgets.

You will build the evals that tell us whether a conversation is actually good, and publish the guidance and reference experiences that show developers how to build natural conversations on the Voice