The role
- COMP
- $130K - $180K
- EQUITY
- Competitive equity
- LOCATION
- San Francisco
- WORKPLACE
- On-site
- EXPERIENCE
- 1 - 8 years
- VISA
- None
- STACK
- Python, React, Next.js
- INDUSTRY
- AI, Security, Cybersecurity, Enterprise, Law, Software Development
/roles — ROLE_393
Founding Engineer, Applied AI Platform
Fast-growing AI security startup that lets large enterprises roll out AI with confidence by vetting vendors
The company
An early-stage security company helping enterprises in regulated industries evaluate, control, and keep watching the AI vendors and tools they buy or build.
- STAGE
- seed-stage
- FUNDING
- seed funding
- TEAM
- ~10 people
- FOUNDED
- 2023
- BACKING
- VC-backed
JD — the work
About the role
In this founding engineering role, you would ship production software to large enterprise buyers, owning each product from zero to one and designing the underlying LLM architecture and data model. Companies in regulated sectors want AI but get stuck in security review, so the platform evaluates their third-party AI vendors, recommends controls, and keeps watching as those vendors change. Customers include some of the biggest corporations anywhere and many top law firms, and the business already generates recurring revenue in the millions. The senior team of about a dozen works in person in San Francisco and is growing toward 20.
What you'll do
- Design and deploy production agent workflows and retrieval pipelines that enterprise customers depend on
- Take charge of the platform's data foundations, from relational schema design to pipelines built to scale
- Carry features and entire products from first version to launch, deciding how to get the result
- Join customer calls and collaborate with sales directly, with no one translating in between
- Act on feedback from major enterprise accounts through rapid, ongoing product iteration
What they're looking for
- 1 to 8 years of software engineering experience
- Experience building LLM-powered systems such as agents or retrieval pipelines in production
- Comfort with relational data modeling and pipelines that scale
- Python plus React and Next.js for full-stack product work
- Drive to ship quickly, own whole problems, and work in person in San Francisco