KEY FACTS- Base salary: $310,000-$340,000
- Equity: 0.30%-0.45% (founding-team tier)
- Location: San Francisco or PA • 5 days in-office
- Experience: 8+ years, 3+ at senior/staff level with system-wide technical influence
- Reports to: VP of Engineering / Bruce Kim (CTO)
Why This Role Is UniqueAs a Staff Engineer, you sit at a rare intersection: working directly with OpenAI's research team on frontier model capabilities while shipping those breakthroughs into a consumer product that touches millions of people's financial lives. Most engineers get one or the other. Here you get both.
What You'll Do- Define the technical direction for a critical domain: either (a) the AI platform layer (orchestration, evaluation, multi-model routing, hallucination mitigation) or (b) the consumer product + data layer (aggregation, enrichment, real-time sync, dynamic UI generation).
- Make architecture decisions that affect the entire engineering team. Own technical RFCs. Set the quality bar.
- Be the technical peer to Bruce Kim (CTO) in your domain. Push back when you disagree. Drive technical clarity.
- Recruit. The best staff engineers attract senior engineers. Bring your network. Be the person others want to work with.
- Ship code. Staff at BankGPT is not an advisory role. You write code, review code, and debug production issues.
- Collaborate directly with OpenAI researchers and other frontier AI leaders to bring the latest breakthroughs in agents, reasoning, and model capabilities into production at scale.
What We're Looking For- 8+ years production engineering with 3+ years at senior/staff level influencing system-wide technical decisions.
- Have built and owned at least one large-scale distributed system (10M+ users, sub-second latency, multi-service).
- Deep expertise in either: (a) AI/ML systems (LLM serving, evaluation frameworks, agent runtimes, RAG at scale) or (b) high-scale data infrastructure (real-time aggregation, streaming, event-driven architecture).
- Extreme AI fluency. Not just using tools - has strong opinions about model architectures, evaluation methodologies, and where the AI capability curve is heading. Technical leadership through influence, not authority. Can get senior engineers aligned on an approach through clarity and evidence.
- Preferred: Top 20 CS degree (or Master's/PhD in relevant field) + startup experience. Exception: deep open-source contributions or significant published technical work.
