/roles — ROLE_332
Member of Technical Staff - Forward Deployed Engineer
Venture-backed AI startup building RL environments that frontier labs use to train finance-capable agents
The role
- COMP
- $200K - $275K
- EQUITY
- 0.15-0.3%
- LOCATION
- San Francisco
- WORKPLACE
- On-site
- EXPERIENCE
- 1 - 5 years
- VISA
- None, Visa transfers
- STACK
- Python, TypeScript, Next.js, Docker, AWS, Microsoft Excel, Microsoft PowerPoint
- INDUSTRY
- AI, Data, Finance, Financial Services, Fintech, Insurance
The company
Small, fast-growing startup building realistic reinforcement learning environments and benchmarks that frontier AI labs use to train agents on real financial and knowledge work.
- STAGE
- Series A-stage
- FUNDING
- $8M raised
- TEAM
- ~10 people
- FOUNDED
- 2024
- BACKING
- VC-backed
JD — the work
About the role
This forward deployed engineer is the technical link between research teams at leading AI labs and the internal platform team. You would join weekly meetings with lab researchers, convert what they need into RL environments for training, and deliver code that powers large, multi-million-dollar projects. The company has grown revenue extremely quickly since launch, so the pace is fast and the work is highly visible. The role is in person in San Francisco.
What you'll do
- Meet with frontier-lab researchers to understand their environment needs and write technical specs
- Build 0-to-1 prototypes and custom environments or tools for specific engagements before they reach the platform
- Team up with project leads in small pods, taking charge of engineering quality and getting requirements production-ready
- Hold RL tasks to high quality standards so environments actually improve frontier models
- Clear delivery blockers through integrations, debugging, and design calls, while protecting the shared platform
What they're looking for
- 1 to 5 years of software engineering experience
- Proficiency in Python and TypeScript, with exposure to Next.js, Docker, and AWS
- Comfort working face to face with researchers and turning loose requirements into specs
- Familiarity with the Excel and PowerPoint workflows common in finance