Location: On-site in San Francisco, CA (Market & Montgomery area)
Travel: 3–4 days per month (mostly US East Coast / Midwest customer sites)
Compensation: $160,000 – $300,000 Base Salary + 75th Percentile Equity
The Company
Our client is a fast-growing, Y Combinator-backed startup ($33M+ in total funding backed by top-tier fintech investors) building "AGI for banking."
They are replacing multi-billion-dollar legacy banking platforms with an AI-native operating system that automates up to 90% of manual lending, underwriting, and account opening workflows. With over $10M+ in contracted ARR and active deployments inside top-10 US banks, they are building the "Palantir for commercial banking."
The Role
This is a high-impact, 0-to-1 engineering role for a builder who wants direct access to real users in one of the largest, least-automated industries in the economy.
Operating like a "mini-CTO," you will embed directly with bank executives, underwriters, and lenders to understand broken, manual processes. You will translate those field learnings into working software, deploying AI agents that replace manual tasks. Everything you build in the field directly shapes and feeds back into the core platform architecture.
Work Split: Roughly 70% building & shipping code and 30% embedded with customers and collaborating with your team.
- Embed in the Field: Spend time alongside bank underwriters and operators to map their day-to-day workflows, bottlenecks, and pain points.
- Build 0-to-1 Applications: Rapidly architect and ship full-stack, AI-powered systems (e.g., digital account opening, credit management automation) directly on top of the platform.
- Own the Lifecycle: Take end-to-end responsibility from initial customer discovery to production deployment and rapid iteration.
- Shape Platform Architecture: Feed field learnings and reusable primitives back into the core platform to power future enterprise deployments.
- 0-10+ Years Experience: Full-stack, product, or forward-deployed engineering experience.
- 0-to-1 Builder Track Record: Proven history of building applications from scratch—whether as a startup founder, employee #1–20 at an early-stage company, or creator of hackathon/side projects with real users.
- Core Tech Mastery: Strong proficiency in TypeScript, React, and Next.js, with a solid understanding of systems design.
- Customer-Facing Instincts: Exceptional verbal communication and the ability to work directly alongside non-technical business users to translate complex problems into technical solutions.
- Education: CS degree required for candidates with 0–3 years YOE (preferably from top engineering programs like Stanford, Berkeley, MIT, CMU, Georgia Tech, etc.). Candidates with 3+ years YOE can substitute with demonstrated technical project depth.
- Prior Forward Deployed Engineer (FDE) experience at companies like Palantir, Scale AI, Databricks, Moveworks, or Glean.
- Former founder, co-founder, or CTO experience.
- Experience with Python, PostgreSQL, and modern LLM frameworks (LangChain, Vercel AI SDK).
Benefits & Package
- Top-Tier Equity: 75th-percentile equity grant in a fast-scaling startup backed by top fintech founders and VCs.
- High-Level Mobility: FDE is treated as equal to (or more advanced than) core product engineering, with full optionality to pivot into core platform engineering anytime.
- Massive Market Scope: Build applications that automate core processes for multi-billion-dollar financial institutions.
- Initial Recruiter Screen (30 mins): Background check, 0-to-1 builder DNA, verbal communication, and logistics alignment (SF in-office + 3–4 days/month travel).
- Technical Screen w/ Engineering Leadership (45–60 mins): Deep dive into a 0-to-1 product you’ve built from scratch and your approach to translating customer problems into scalable code.
- Systems Design & Coding (60–90 mins): Practical full-stack coding (TypeScript, React, Next.js, Python) and AI system/agent architecture.
- Final Onsite (Half Day — San Francisco): In-person pairing session at the SF office, meeting the founding team, and working through a collaborative customer deployment simulation.