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Founding SW Engineer

San Francisco, California ยท Computer/Software
The mission of our first engineer is to help us build the features we need to scale. As the first hire, the work this person does will become core infrastructure and strongly influence our engineering for years to come. This person will likely lead a team as we scale.

Expected outcomes
- Architect and implement whole parts of the app from scratch, such as web-based, on Windows, and Sharing UX. Take responsibility for quality, delivery, and maintenance. These should be delivered quickly and improved iteratively.
- Collaboratively improve our existing codebase and practices, explaining options to the rest of the team and obtaining buy-in when making significant changes. However, the candidate should take the initiative to suggest improvements proactively while acknowledging priorities and accepting decisions.
- Should be shipping features weekly, daily. This person needs to be an energetic startup engineer, productive in our codebase, and capable of shipping code to production by day two.
- We should be comfortable with this engineer speaking with customers and conducting customer research independently, without requiring a product manager.
- Conversations with the engineer should be efficient, with a strong grasp of technical, product, and market concepts, as well as second and third-order effects.

About you
  • 2-10y of heavy JavaScript work experience. Has worked on a single project for 2y+ and can explain how your early code evolve and trade offs
  • has own and shipped product completely independently without needing product manager and tech lead
  • use Gen AI regularly and can ask good questions and prompt
  • interested in what we do
  • Strong founder DNA - e.g. prior founder yourself, early start up employees, can demo your side projects (eg. Product Hunt, Kickstarters),
Company Tech Stack
* Electron (Javascript + understanding of desktop)
* Node.js
* Svelte for UI
* Swift/C++ for native applications & ML inference
* Some python for machine learning prototyping, not for deployment
* Might use ONNX for future ML models

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