Staff Product Manager, Agentic Experiences (Former Engineer) - Deepgram

Company Overview

Deepgram is the leading platform underpinning the emerging 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.

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 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. 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.

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 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.

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, trial-key and token defaults, programmatic key provisioning, console onboarding, and verification tooling.
• Set requirements for what the agent experience needs from shared developer platforms (SDK ergonomics, agent-readable documentation, llms.txt, MCP server, CLI, skills package, and starter templates) and prototype changes directly.
• Stand up the operating system your work runs on: rhythms of business, data-driven optimization, and experimentation platforms.
• 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, 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.
• Are energized by being early and defining the practice rather than inheriting it.

It's Important to Us That You Have

• Excellent product management judgment: Track record of owning product roadmaps, setting direction, deciding under uncertainty, shipping outcomes, and leading cross-functional teams without direct authority.
• A former engineer's depth (required): Prior background as a senior software engineer or higher. Ability to architect and ship production systems, read and write code, and reason with engineering at their level.
• Deep AI fluency, proven by shipped work (required): Hands-on experience building and shipping public AI software beyond prompts (agents, MCP servers, CLI tools, evaluation harnesses, or model-integrated tools) with a verifiable GitHub profile.
• System building capability: Proven ability to stand up a complete system from scratch (rhythms of business, reporting, optimization, and experimentation).
• PLG and developer-product fluency: Deep understanding of product-led growth and how developers and AI agents adopt APIs.
• Rigorous data skepticism: The judgment to rigorously question metrics or passing tests before building on them.
• Executive communication: Clear, decisive communication that leads with decisions and withstands pushback.

It Would Be Great If You Had

• Experience building specifically for AI agents as the consumer (MCP servers, agent harnesses, CLI tools, agent-readable docs, tool definitions, or evals).
• Experience with voice, audio, or real-time streaming systems.
• A track record of open-source contributions with real adoption.
• Experience in a company with both self-serve and enterprise motions.