Full Stack Engineer

Fluency•San Francisco, CA

63d•$150,000 - $220,000•Onsite

About The Position

Fluency is enabling the autonomous Enterprise. (in person). You're needed to help pioneer a new software category that will change how enterprises work. Welcome to the data layer of the future. Fluency is looking for a next-level full-stack engineer to build the autonomous enterprise. You'll be working on problems that have no established solutions. We're processing terabytes of workflow data per enterprise customer in real-time - systems that map, relationship, contextualize, and analyze work patterns across entire orgs. Think human genome project, but for enterprise workflows. You'll invent new data primitives and paradigms. This means designing novel data structures for representing work, building pipelines that process billions of events per day, and writing whitepapers on approaches that don't exist yet. You're operating at the bleeding edge of data science where the playbook hasn't been written. We're backed by T1 VCs like Accel + more, and are hitting an inflection point with Enterprises all around the globe. You'll work directly with founders and our engineering team. The technical challenges are unprecedented: real-time processing at massive scale, creating a universal taxonomy for work across every industry, and building systems that can handle the most complex enterprise data environments on earth. About the Role We're looking for someone with: Strong TypeScript skills (advocate for type safety encouraged) NestJS, React, Vite, Tanstack SQL proficiency Cloud Experience (AWS + GCP preferred), Docker, Actions PostgresSQL LLM API experience (major providers, not training level) Computer Science Background - with caveat. If you don't have a CS background, you're challenged to beat one of the founders in a 1:1 coding duel on a whiteboard. This isn't DS&A (you're a full stack engineer, who care what big O of N this arbitrary sort runs in). But you will be put to the full-stack test. Our founders have no technical background, and run as the benchmark. There will be an expectation to stay up to business context, which could involve: Watching key customer calls Interacting with customers! Helping with product thinking