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# Founding AI Engineer

- **Company:** David Joseph & Company
- **Location:** San Francisco, CA, United States
- **Salary:** $160,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Information Engineering, TypeScript, Backend
- **Published:** August 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=da746bc6ad3c52d7

## About the Role

* Highly independent and self-unblocking; able to direct your own work with minimal oversight.
 * Fast-moving and prototype-oriented; you ship experiments quickly.
 * Strong evaluation discipline and genuine research taste for high-risk, high-reward work.
 * Either a strong software engineer eager to grow into ML/AI, or an ML/AI engineer who already prototypes fast.
 * Comfortable across the stack (TypeScript front-end and back-end).
 * Genuinely motivated by the mission of making housing more affordable.
 * Able to work on-site in San Francisco full-time, approximately 55 hours/week with some weekend availability.

Nice to Haves

 * Experience at an autonomous-vehicle company, where rigorous evaluation is second nature.
 * Background in highly regulated applied-AI domains (e.g. medical or legal) where evaluation discipline is critical.
 * Climate-tech or other mission-driven startup experience.
 * Strong academic background.
 * Genuine curiosity for digesting dense technical and regulatory material (building codes, technical diagrams).

## Description

A deeply self-directed founding AI engineering role owning the full experiment loop to improve the accuracy of the client's multimodal blueprint-compliance agents. The work is heads-down and technical, with a small amount of weekly user contact - not a forward-deployed role.

What you'll be doing

 * Spend the majority of your time improving the accuracy of the multimodal blueprint-compliance agents - building autoresearch, improving evals, and running sweeps on experimental features you design.
 * Own the full experiment loop: generating ideas, implementing them, and rigorously analyzing results on the eval framework.
 * Become a domain expert on the parts of the building code that matter (accessibility, wildland-urban interface, structural and fire safety).
 * Wear hats as needed: computer-vision experiments, lightweight data engineering, internal tooling, and webapp improvements.
 * Roughly two hours a week of user contact and product dogfooding.

Tech stack: Tech-stack agnostic; TypeScript across front-end and back-end. Modern AI coding tools used throughout.


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