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Sarsfield Group in San Francisco is seeking a Principal/Staff+ Engineer to own architecture and delivery of an entire AI-driven fintech domain. You will build and ship production AI systems, lead a pod, and stay deeply hands-on with code.
This on-site role emphasizes fast execution, high ownership, and close collaboration with Product to align outcomes. Experience with distributed systems, frontier AI tools, and end-to-end ownership is essential.
Looking for experienced builders only. Join a small, elite, execution-focused team and personally own an entire technical domain at an AI-native fintech pushing agentic AI into one of the highest-stakes industries.
This role is primarily on-site in San Francisco (3-5 days/week), with remote flexibility for exceptional candidates.
Own architecture and engineering for an entire technical domain.
Architect, build, and ship production AI systems alongside your team.
Lead a pod through technical credibility while remaining deeply hands-on with code.
Build AI agents across voice, chat, retrieval, evaluation, and computer use.
Own the technical bar for quality, reliability, and velocity.
Partner with Product as an equal owner of outcomes.
Use Claude Code, Cursor, and frontier models as part of the daily engineering workflow.
Staff or Principal-level Software Engineer with 6–14 years of experience.
Experience scaling with an early-stage startup (Series A–C).
Owned a critical system or product end-to-end from 0→1.
Strong distributed systems and software architecture fundamentals.
Deep, daily use of frontier AI tools such as Claude and Cursor.
Strong hands-on engineering skills, ideally across Python, Node.js, and React.
Comfortable leading technically without moving into pure management.
Hands-on technical founder experience.
Conversational AI, voice AI, or agentic systems experience.
Experience building production LLM or AI systems.
BS/BA in Computer Science or a related technical field.
MS or PhD in a related technical field.
Experience building high-scale fintech or financial infrastructure.
AI-native – frontier AI tools are part of the standard engineering workflow.
Hands-on – senior technical leaders still architect, code, review, and ship.
High ownership – own an entire domain rather than a narrow piece of a system.
Small senior team – engineering is organized into high-leverage pods.
Production-focused – real AI products serving 100+ financial institutions.
Early-stage impact – Series A and already cash-flow positive.