• San Francisco (Hybrid)
• Founding/Staff Engineer
• $200-300k base
Our client is an AI-native research and product lab on a mission to redefine how global finance operates. Backed by a team that includes former Google DeepMind researchers and engineers, they are applying frontier AI to some of the most complex, high-stakes problems in finance.
This is a true founding engineer opportunity. Youll help turn cutting-edge AI research into production systems used by real financial institutions, while shaping the technical foundation, standards, and culture from the ground up.
What youll do
• Build core product features end-to-end, spanning frontend, backend, and infrastructure using TypeScript, React, and Node.js.
• Productionize frontier ML research, working closely with researchers to ship robust, user-facing AI systems.
• Design and own critical services, architecting reliable, scalable infrastructure with Docker and Kubernetes.
• Set the engineering bar as a founding team memberestablishing standards for code quality, testing, and development workflows.
• Prototype rapidly, ship decisively, and iterate continuously, collaborating closely with product managers, designers, and researchers.
• Make thoughtful architectural decisions, including rewriting systems when it meaningfully improves long-term quality and simplicity.
The Ideal Candidate
• Have built polished, high-performance web applications end-to-end, from design through production deployment.
• Are deeply fluent in modern frontend development, including TypeScript, React, Tailwind, and Next.js.
• Can comfortably design and evolve backend microservices (Node.js or Python) to deliver features end-to-end.
• Are an expert in at least one statically typed language and have strong instincts around type safety, maintainability, and correctness.
• Have experience deploying production systems with Docker and Kubernetes on GCP
• Use AI as a productivity multiplierbut critically evaluate AI-generated code, catching bugs and calling out poor design.
• Thrive in a high-performance, high-ownership environment alongside other strong engineers.
• Enjoy tackling technically deep, ambiguous problems and thinking carefully about product tradeoffs.
Nice To Have
• Experience working with ML or applied research teams, or familiarity with ML pipelines.
• Background in fintech, trading, quant platforms, or other high-stakes domains.
• Prior experience as an early-stage or founding engineer.
