About the Role
Build the internal platform that turns institutional finance expertise into structured training data, the tools, pipelines, and interfaces the data engine runs on.
A full-time role based at Qofi's New York office, working alongside operators from top investment banks and private equity firms and engineers from leading AI labs.
Qofi builds the highest-precision financial-reasoning data in the world, and the platform and deployments that put it to work inside institutions.
High ownership from day one, in a flat structure where ideas move from whiteboard to production without committees.
Base salary plus meaningful equity and full benefits. Range is a placeholder pending confirmation.
On-site at Qofi's New York office, alongside the team building the data engine.
Full-time. Rolling start, the team moves quickly once there's a fit.
What You'll Do
Design and ship full-stack features across the data-production platform, from expert-facing task interfaces to internal review and QA tooling.
Build reliable services and data models that move deal-level financial work through structured pipelines at scale.
Partner with research and operations to translate new data formats into production workflows quickly.
Own features end to end, from technical design through deployment, monitoring, and iteration.
What We're Looking For
3+ years building production web applications, with strong command of TypeScript and a modern framework such as React.
Experience designing APIs and relational data models (e.g. Node.js, PostgreSQL) in a production environment.
A bias toward shipping, comfortable owning ambiguous problems end to end in a fast-moving environment.
Interest in applied AI and financial data; no finance background required.
Hiring Process
Send a resume and a short note on why this role, about five minutes.
A conversation about your background, the role, and what you're looking for.
Technical and team-fit conversations with the people you'd work with directly.
A clear decision quickly, with an offer and a start date that works.