[All remote jobs](https://jobicy.com/jobs.md)[![Deepgram logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/12/WRILS-201212160008-406229.jpg)](https://jobicy.com/company/deepgram.md)[Deepgram](https://jobicy.com/company/deepgram.md) # Staff Conversational Designer AI Summary Deepgram is seeking a Staff Conversational Designer to define the interaction principles and quality standards for production voice agents. The role owns persona, turn-taking, interruptions, repair flows, confirmation strategies, and latency-aware pacing across the speech pipeline. This staff-level individual contributor will partner closely with ML and engineering teams while creating evaluation methods, reference experiences, and developer-facing guidance. Success depends on deep experience with LLM-based voice agents, ASR/LLM/TTS systems, measurable conversation quality, and influential technical communication.[Apply for this job](#job-application)[View company](https://jobicy.com/company/deepgram.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 180k–240k / yrDepartment[Web, UI & UX Design](https://jobicy.com/categories/web-app-design.md)EmploymentFull TimeExperienceDirectorPublished11 Nov 2026Apply before11 Dec 2026Listing views33Application actions2Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. ### Company Overview [Deepgram](https://jobicy.com/company/deepgram.md) is bringing the world’s most natural interface, voice, to the technology we use every day. Our speech models and real-time infrastructure power AI systems that keep up with the way people actually speak. More than 5,000 organizations run conversational voice AI on Deepgram in production, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Cresta, Granola, and Jack in the Box. The Deepgram Voice Agent Platform brings together speech-to-text, text-to-speech and speech-to-speech, with voice-native foundation models available through cloud APIs or self-hosted and on-premises deployments. Built for accuracy, low latency and cost efficiency, Deepgram makes high-quality voice experiences practical to build and run at scale. More than 650,000 developers have used Deepgram to process more than 200,000 years of audio. Every day, more of the world’s conversations with AI run on our models. Operating Principles: Deepgram is a research company that productizes as fast as possible. Four Operating Principles shape how we think, decide, and work together: * Compress before you communicate. You think it through first, then lead with the bottom line. * Resist entropy. You question what already exists before adding more process or tools. * Solve the category. You fix recurring problems at the source, not one case at a time. * Work at the frontier. You go after problems no one has solved yet. We look for people who already work this way, and these principles shape how we grow and evaluate our team. ### AI-First by Default We build AI that millions of people talk to, and we run the company the same way. AI is how we centralize work here, and is core to how we operate. That means more than using the tools. We expect you to: * Build, not just use. Design your own workflows and agents, and use AI to remove whole categories of work instead of doing the same work faster. * Own the output. AI can speed up the work. It doesn’t make anyone less accountable for it. You understand, verify, and stand behind everything you share, including what an agent produces for you. * Spend the time you get back at the frontier. The capacity AI creates goes toward problems no one has solved yet. * Keep pace. Models and tools change every month, and so will your work. You adopt what’s new quickly and drop what no longer earns its place. We judge AI by what it helps you deliver and whether you stand behind the result, not by how often you use it. In interviews, expect to walk us through a workflow you built and where you drew the line between AI and your own judgment. Note: This is a remote role based in Pacific Time, with a preference for candidates located in San Francisco. ### About The Role Deepgram builds the models and APIs that put voice agents into production at scale. What decides whether those agents feel human is not a screen. It is whether the agent knows when you have finished speaking, what it does when you cut it off, how it recovers from a misheard word, how it confirms something consequential before acting, and how it covers the milliseconds it cannot remove. Today those decisions live inside prompts and pipeline config, made ad hoc by whoever is closest to the problem. No one owns them end to end. We are hiring a Staff Conversational Designer to own them. You will define how Deepgram’s voice agents converse: persona, turn-taking, repair, confirmation, and pacing. You will work directly with ML and Engineering on the tradeoffs that make those 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 Agent API. This is a leading edge role. Very few companies have a titled equivalent. You will be defining this discipline at Deepgram, not inheriting it. You’ll report directly to the Director of Product Design. This is a Staff IC role, and your impact shows up mostly in the leverage you create for others: the patterns our own experiences run on, and the guidance our customers build against. Your first chapter: a documented persona and voice system, and turn-taking and repair behavior designed and shipped with Engineering. From there, scope expands into conversational-quality evals and developer-facing guidance. ### 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 ### You’ll Love This Role If You * Believe conversation is an interface with real craft behind it, not a prompt someone tunes on the side * Want the hard real-time problems: endpointing, barge-in, and the half-second you cannot design away * Get energized by being foundational, defining what good means for a discipline that does not exist here yet * Think the fastest way to raise quality is to make it measurable, then make it repeatable * Are excited by a category still inventing its interaction patterns, where the work is invention rather than iteration ### It’s Important To Us That You Have We care more about expertise and leadership than years of experience. * 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 ### It Would Be Great If You Had * 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 Notice: We’re aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @[deepgram.com](http://deepgram.com) email address. If you’ve received a message claiming to be Deepgram, please forward it to careers@deepgram.com. Show more [Apply now >](https://jobicy.com/jobs/161382-staff-conversational-designer.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a pioneering staff-level role in an emerging discipline, requiring ownership of ambiguous real-time conversational challenges with direct product and technical consequences. The candidate must influence ML and engineering partners while establishing reusable standards for an entire platform. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$210,000US market range (per year)$175k–$260k0$286k AI insightThe employer discloses a credible annual base-pay range of USD 180,000 to USD 240,000, with a midpoint of USD 210,000. Estimated US market compensation for a staff-level conversational or voice-AI design specialist is approximately USD 175,000 to USD 260,000 annually, depending on location, production voice-AI expertise, and scope of technical leadership. ## Core skills Skills and capabilities most closely associated with this opportunity. [Conversational design](https://jobicy.com/jobs?search_keywords=Conversational%20design.md)[Voice user interfaces](https://jobicy.com/jobs?search_keywords=Voice%20user%20interfaces.md)[LLM voice agents](https://jobicy.com/jobs?search_keywords=LLM%20voice%20agents.md)[ASR](https://jobicy.com/jobs?search_keywords=ASR.md)[Text-to-speech](https://jobicy.com/jobs?search_keywords=Text-to-speech.md)[Turn-taking design](https://jobicy.com/jobs?search_keywords=Turn-taking%20design.md)[Barge-in handling](https://jobicy.com/jobs?search_keywords=Barge-in%20handling.md)[Conversational repair](https://jobicy.com/jobs?search_keywords=Conversational%20repair.md)[Conversation quality evaluation](https://jobicy.com/jobs?search_keywords=Conversation%20quality%20evaluation.md)[Transcript analysis](https://jobicy.com/jobs?search_keywords=Transcript%20analysis.md)[Technical documentation](https://jobicy.com/jobs?search_keywords=Technical%20documentation.md)[Cross-functional leadership](https://jobicy.com/jobs?search_keywords=Cross-functional%20leadership.md) Sample interview questionsHow would you balance fast endpointing with the risk of interrupting users in a voice agent?I would treat endpointing as a use-case-specific optimization problem rather than a fixed threshold. I would combine acoustic and semantic signals, test interruption and latency metrics, review transcripts, and define different policies for low-risk and high-stakes tasks. Describe how you would design a repair flow after an agent misunderstands a user. I would first classify the failure type, such as low ASR confidence, ambiguous intent, or unsupported request. The repair should acknowledge the uncertainty concisely, preserve useful context, ask the smallest clarifying question possible, and offer a safe fallback when confidence remains low. What metrics would you use to evaluate conversational quality for a production voice agent? I would use a combination of task completion, interruption rate, false endpoint rate, repair success, latency, escalation or abandonment, and qualitative transcript review. Metrics should be segmented by use case and paired with a structured failure taxonomy so that teams can prioritize systemic improvements. How do you influence ML and engineering partners when you do not manage them directly? I create shared artifacts that make tradeoffs visible, including behavior specifications, sample dialogs, measurable acceptance criteria, and evidence from evaluations. I frame recommendations in terms of user impact, technical constraints, and repeatable platform leverage rather than personal preference. How would you create developer-facing guidance for conversational design on an API platform? I would provide clear principles, implementation patterns, anti-patterns, annotated examples, and reference agents that developers can adapt. The guidance should connect user-facing behavior to relevant API and pipeline controls, explain tradeoffs, and evolve from observed production failures. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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