Founding Engineer

Founding Engineer

Full-time. San Francisco, in person.

Screenpipe is building open computer history: a local record of what happens on your computer that gives AI agents useful context. We capture screen and audio activity, make it searchable, and connect it to the tools people already use.

We are looking for a founding engineer who can take a messy user problem, decide what matters, and ship a reliable solution. You will work directly with the founder and own substantial parts of the product, from implementation through release and feedback from real users.

What you will own

- Build the core desktop product: capture, local storage, search, and the interfaces that make computer history useful.
- Improve reliability and performance across real machines. Investigate crashes, memory and CPU usage, audio issues, and failures that are hard to reproduce.
- Build APIs, integrations, and AI workflows that turn captured context into something people use repeatedly.
- Take features from a conversation with a user to a shipped result. Talk to users, make tradeoffs, and verify that your work solves their problem.
- Keep the codebase understandable as it grows. Write focused tests, improve boundaries between components, and make systems easier to debug and maintain.
- Treat privacy and data handling as core engineering concerns. Understand what is captured, where it is stored, and what an integration can access.

What we are looking for

- You have built and shipped software you can explain in detail. Show us your contribution, the difficult decisions, and what happened after release.
- You can move between product interfaces and backend or systems work. Our stack includes Rust, TypeScript, React, and Tauri. Depth in part of the stack and the ability to learn the rest matter more than knowing every tool already.
- You can debug unfamiliar systems, form a hypothesis, inspect evidence, and verify a fix.
- You use AI coding tools with judgment. You can explain the code they produce, recognize failure modes, and check correctness.
- You take initiative, communicate clearly, and change your mind when evidence warrants it.
- You can work in person in San Francisco. Please state your current location and when you could start working here.

We care about demonstrated work and ownership. A particular degree, employer, or number of years is not a substitute for those things.

What to include when you apply

Please keep answers concise. Links, bullets, and public or anonymized examples are welcome.

1. Two or three things you built, with your exact contribution and an outcome you verified. Include a repository, demo, or technical write-up where possible.
2. One difficult bug or engineering tradeoff. How did you investigate it, and how did you check the result?
3. Your actual AI setup: models, coding agents, editors, MCP servers, memory, skills, or automations. Show one unusual workflow you use repeatedly and where it still fails.
4. Roughly how many AI tokens you use in a typical week, or your approximate spend and usage pattern if token counts are unavailable. Explain what you produce with it. These numbers are context, not a hiring threshold.
5. Roughly how many books you read or listened to in the past year, two or three favorites, and an idea that changed how you think or work. Tell us what you are learning now.
6. A time user feedback or evidence changed your technical or product opinion. What did you change?
7. What you would investigate first in Screenpipe, and why.

Do not include credentials, private prompts, or confidential customer or employer information.

Explore the project: https://github.com/screenpipe/screenpipe