Staff Product Manager, Agentic Experiences (Former Engineer)

Bazeta; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Deepgram is seeking a Staff Product Manager with an engineering background to own the agent experience from discovery through verification. You will prototype and work closely with engineering to ship AI-native tooling that scales as agent behavior evolves.

You will build systems to measure funnel stages, refine onboarding, and define requirements for SDKs, docs, and CLI tooling, partnering with platform teams to accelerate adoption and reliability.

Qualifications

• Have a strong engineering foundation and prior senior software experience.
• Demonstrate proven product management judgment and roadmapping能力 (ship outcomes, lead cross-functional work).
• Show deep AI fluency with shipped AI software beyond prompts or docs.

Responsibilities

• Own the agent experience across discovery, onboarding, production use and verification.
• Build and maintain systems to measure and optimize the agent funnel.
• Define product surfaces: signup/authentication, trial-key defaults, provisioning, onboarding, and verification tooling.
• Specify requirements for developer platforms (SDK ergonomics, docs, MCP server, CLI, tools packages) and prototype changes.
• Create an operating system for data-driven optimization and in-house experimentation.
• Translate agent behavior into fast feedback loops to improve the product.
• Advocate for agents as users, understanding needs and failure points.

Skills

Engineering background

Product management

AI fluency

Tools

SDK tooling

CLI

MCP server

Job description

# Staff Product Manager, Agentic Experiences (Former Engineer)United States1 hour agoID 5195591Price on request## DetailsEmployment type: Full-timeRemote: YesCompany: DeepgramLevel: Director## DescriptionCompany 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. The Opportunity The way developers find and adopt an API is changing. More and more, an AI coding agent discovers us, chooses the provider, writes the integration, and consumes our API, often with no human ever at the console. Deepgram is looking for a Staff Product Manager to own our product experience for that agent across its whole life with us: how an agent discovers and chooses Deepgram, how it integrates, how it uses the product in production, and how it verifies its own work. You will own that experience end to end, and you will build the system that keeps improving it as agent behavior changes. You report to the VP of Self-Serve. This is a product management role in the conventional sense: you own the product, its direction, and its decisions, and engineering builds it. Two things set the role apart, and both are required — you are a former engineer who still builds to think and to prove a point, and you are deeply AI-native, with shipped work to show for it. You will prototype, read and write code, and reason with engineering at depth; your job is to own the product, not to be its implementing engineer. What You'll Do - Own the agent's experience of Deepgram across its lifecycle — discovery and recommendation, integration and onboarding, production use, and verification. - Stand up a system that measures and optimizes every stage of the funnel for agents, and keep it current as agent behavior changes. - Own the product surfaces specific to the agent experience: signup and authentication, the trial-key and token defaults and programmatic key provisioning, console onboarding, and the verification tooling that lets an agent confirm its integration is actually correct. - Set the requirements for what the agent experience needs from the shared developer platforms — SDK ergonomics, the agent-readable documentation and llms.txt, the MCP server, the CLI, the skills package, and starter templates — and prototype the changes directly, in partnership with the team that owns those platforms. - Stand up the operating system your work runs on — the rhythms of business, data-driven optimization, and the experimentation platform — by building it in-house or by researching and deploying the best tools available. - Turn the scale of agent traffic into fast feedback loops, so the product improves as agents use it. - Bring the product's point of view on agents as users: what they need, where they fail, and what to change, grounded in how models actually retrieve, choose, and integrate. You'll Love This Role If You - Were an engineer, moved to product to own outcomes, and never stopped building. - Think like an architect and can design and stand up a self-optimizing system across discovery, onboarding, and integration. - Have felt, first-hand, how an AI agent succeeds or fails at a real integration, and have strong opinions about why. - Want to own a product that is becoming the front door of the business, at the moment it is becoming that. - Are energized by being early — defining the practice, not inheriting it. It's Important to Us That You Have - Excellent product management judgment. You own product and roadmap, set direction, decide under uncertainty, ship outcomes, and lead cross-functional work without authority. You can show the results. - A former engineer's depth (required). You were a senior software engineer, or more, before you moved to product. You architect and ship production systems, you read and write real code, and you reason with engineering at their level. You are not a vibe coder who assembles what a tool generates. - Deep AI fluency, proven by shipped work (required). Y ou have personally built and shipped AI software that goes well beyond prompt files and markdown — agents, MCP servers, CLI tools, agent and evaluation harnesses, real model-integrated tools — and it is public. Send us the GitHub; we will read the code, the commits, and the design.... Source: Jobicy (https://jobicy.com/jobs/159511-staff-product-manager-agentic-experiences-former-engineer)This listing comes from a partner feed. Apply on the source website.