# Staff Product Manager, Agentic Experiences

**Company:** [Deepgram](https://hotfix.jobs/companies/deepgram)
**Location:** Remote
**Role:** Product Management
**Salary:** $200k – $268k/yr
**Experience:** 7+ years
**Skills:** Product Management, AI Agents, mcp servers, cli tools, LLMs, SDKs, APIs, Product-Led Growth, experimentation platforms, voice ai
**Posted:** 2026-07-29

> Staff Product Manager owning end-to-end agentic experiences for Deepgram's Voice AI APIs. Former senior engineer who still prototypes and ships AI agents, MCP servers, and evaluation tools; defines discovery, integration, and verification for AI coding agents while building self-optimizing measurement systems.

## Job Description

## Responsibilities
- 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.

## Requirements
- 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.
- Deep AI fluency, proven by shipped work (required). You 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.
- Proven ability to stand up a complete system from scratch — the rhythms of business, the reporting and optimization, the experimentation platform — yourself or in-house, or by researching and deploying the right tools.
- PLG and developer-product fluency. You understand how developers, and increasingly their agents, adopt APIs, and you understand product-led growth.
- The judgment to distrust a number or a passing test before you build on it. You ask whether it is real, as a reflex.
- Clear communication with executives: you lead with the decision, keep your method in reserve, and hold up under pushback without either caving or digging in.

## Nice-to-Haves
- Built specifically for AI agents as the consumer — MCP servers, agent harnesses, CLI tools, agent-readable docs, tool definitions, or evals for agent output.
- Experience with voice, audio, or real-time streaming systems.
- A track record of open-source work with real adoption.
- Time in a company with both a self-serve and an enterprise motion.

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**Canonical:** https://hotfix.jobs/jobs/705b0e2a-9e62-496f-955d-9ab4e6d9aa28