Staff Engineer

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)
  
  

The barrier to real financial intelligence has never been data. Banks have always had it. It's never been AI — that's a commodity now. The barrier is trust. Building a system accurate enough to advise someone on their mortgage, fast enough to feel like a conversation, and safe enough to actually move their money.

BankGPT is building that system. Personal financial intelligence for every American — an AI that aggregates every account, understands the complete picture in real time, and acts autonomously on financial goals. 55% of Americans already use AI for financial tasks. No product today connects that intelligence to their real data. We do.

Why This Role Is Unique

As a Staff Engineer at BankGPT, 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.