Staff Conversational Designer
## **公司概述** Deepgram 是支持新兴数万亿美元的语音人工智能经济的领先平台，为语音到文字 (STT),文本到语言 (TTS) 提供实时 API,并建立规模级生产级语音代理。超过200,000名开发人员和1,300多个组织构建由 Deepgram 发动的语音产品，包括 Twilio,Cloudflare,Sierra,Decagon,Vapi,Daily,Cresta,Granola 和 Jack in the Box.Deepgram 的语音原生基础模型通过云 API 或作为自主托管和本地软件访问，具有无与伦比的准确性，低延迟率和效率。支持由全球领先投资者和战略合作伙伴领导的 C 系列，Deepgram 处理了超过50,000年的音频并转录了超过1万亿字。世界上没有组织比 Deepgram 更好地理解声音.## **公司运营节奏** 在 Deepgram,我们预计人工智能优先思维方式 AI 使用和舒适性不是可选，它们是我们如何操作，创新和测量性能的核心。在 Deepgram 工作的每个团队成员都应该积极使用和实验高级人工智能工具，甚至构建自己的日常工作中。我们测量人工智能如何有效地应用以提供结果，并且持续的创意使用最新的人工智能功能是成功的关键。候选人应该很舒服快速采用新模型和模式，将 AI 集成到他们的工作流程中，并不断推进这些技术所能做的界限。此外，我们随着人工智能的步伐而发展。变化速度快，你可以期望你的日常工作同样迅速发展。如果你不热衷于实验，适应，立足思考和不断学习，或者你正在寻找具有传统9至5规范性的东西，则这可能不是正确的角色：**注释：这是一个远程角色，基于太平洋时间，喜欢位于旧金山的候选人。*##** **关于角色** Deepgram 构建了将语音代理投入规模生产的模型和 API.决定这些代理是否感觉到人类不是屏幕。这是否代理知道你说完话的时候，它会做什么当你切断它时，如何从一个错误听到的话中恢复，如何确认一些后果之前行动，以及如何覆盖不能删除的毫秒。今天这些决策生活在提示和管道配置内，由最接近的人进行特别。
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## **Company Overview**
Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.
## **Company Operating Rhythm**
At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.
Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.
Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.
**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._