Senior Engineer (AI Product)

## The Role

We're hiring a **Senior Engineer (AI Product)** to own new AI products end to end, the kind that help engineers debug and fix issues in a fraction of the time it takes them today. You'll start from a rough idea, research what's possible, build a prototype, and put it in front of real users within days rather than quarters. This is a role for someone who treats a model as a tool to solve a user's problem, not a demo to show off.

## What You'll Do

- Own 0 to 1 AI products that help engineers find and fix bugs in far less time than they spend now
- Research what's possible, build prototypes fast, and share them with users to validate before you commit
- Train and fine-tune models for code generation, and figure out where an LLM genuinely helps versus where it just adds latency and noise
- Go from idea to in-production in a couple of weeks, then watch the metric move
- Dogfood Jam every day; a dev tool built by engineers who feel the same pain they're solving

## What We're Looking For

- Senior engineer who has shipped real product, ideally with an AI or ML surface users actually depend on
- Comfort across the stack: you can build the model-facing backend and the frontend a user touches
- You dig into a hard technical problem and can explain it to someone who isn't in the weeds
- You prototype to learn, not to impress, and you kill the idea that didn't work without ceremony

## Strong Advantages

Nice-to-haves, not strict requirements.

- Hands-on with LLMs for code generation: prompting, fine-tuning, evals, keeping cost and latency honest
- TypeScript across a real codebase (extension, web app, backend services)
- You keep up with the AI space because you enjoy it, not because a role told you to

## The Stack You'd Touch

React with Styled Components on the frontend, TypeScript across the extension, web app, and backend, GraphQL for the API, MobX state tree to sync state across the browser extension, Cloudflare Workers at the edge, and Node, Postgres, and Redis on Google Cloud with Kubernetes.

## Your Teammates

Senior ICs who love the craft, a few ex-engineering-directors who went back to building, and early Cloudflare engineers and PMs. Serious about the customers, the product, and the team, and not that serious about much else.

## Location

Remote in the US, with in-person time in San Francisco if you want it.

## Next Steps

Tell us about an AI feature you took from idea to something users leaned on, and how you knew it was working. One real story beats a tidy resume here.