Product Manager, Developer Experience

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.

THE ROLE

Product at Baseten is a nascent function. Our company today has a strong engineering culture, is heavily customer obsessed, and moves fast. We're building the product function now, and you'd be one of the first people who will help define it. You'll work directly with our founders and with some of the best systems and infrastructure engineers in the world, and you'll set the standard for building great AI infrastructure. PMs at Baseten don't sit above engineers. You earn ownership by being technical, finding the truth in front of customers, building great cross-functional relationships, and shipping great product experiences.

Getting a model into production still takes real expertise: choosing a serving engine, sizing hardware, tuning it, wiring it into an app. We want a developer to go from "it runs on my laptop" to "it's serving production traffic" in minutes, on their own. You'll own the entire experience a developer touches to deploy and iterate: the CLI and SDKs, the console, onboarding, model discovery, deployment configuration, Truss, and the increasingly agent-driven ways developers build. Your job is to make Baseten synonymous with great DevEx and make it effortless for far more developers to self-serve deploy models on Baseten than can today.

This role fits someone who gets technical by instinct and does whatever it takes to ship for customers, not only strategy, UX, or docs. You'll define the design system and the patterns from scratch rather than work inside ones someone else built, and you're obsessed with improving your product craft with AI.

EXAMPLE INITIATIVES

Take a look at these blog posts written by members of our Product and Engineering teams:

Building multi-component AI workflows at scale with Chains

Announcing Baseten for Model Labs

Introducing canary deployments on Baseten

RESPONSIBILITIES

Collapse time to production, taking a developer from first sign-up to a running, maintained production deployment and driving down the time it takes to get there.

Make the CLI and SDKs the primary way developers and their AI agents build on Baseten, converging the authoring surfaces (CLI, console, Truss, config.yml, model.py , chains.py ) into one coherent path.

Make a developer's first run effortless across onboarding, model discovery and deploy via the Model Library, and a first deploy where errors surface clearly and builds show progress.

Own the deployment lifecycle that lets teams ship safely, including environment promotion from dev to staging to prod, version history, an artifact and model registry, reproducible deployments, and the progressive delivery controls developers set and read: canary, shadow, A/B, scheduled promotion, and one-gesture rollback.

Define how developers compose multi-model apps through Chains and the DevEx for developers building multi-modal agents and applications.

Grow self-serve deployment across FDEs and customers by living in customer conversations and turning deploy-and-operate friction into roadmap, so work that needs an FDE today becomes something a developer does alone.

REQUIREMENTS

5+ years building developer-facing or technical products, as a product manager or as a product-minded engineer.

Built dev tools as an engineer before becoming a PM, shipping SDKs, CLIs, APIs, or platform surfaces with your own hands.

Proof of dev tooling and dev products you've shipped and take pride in.

Genuine taste for developer experience across both local (CLI) and UI, with a specific example of where you made something complex feel simple.

Strong opinions on CLI, API-first, and agent-first design, treating the coding agent as a first-class user rather than a feature.