ironquill.tech/board

$ cat jobs/staff-software-engineer-cambly-7336ef705da4.json

Staff Software Engineer

Cambly·US·San Francisco·senior
pythonreactnext.jsflaskfastapiaws
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STAFF SOFTWARE ENGINEER About Cambly: Our mission is to bring high-quality English education to every English learner in the world at the touch of a button. Think of us as the Airbnb that matches English students with English tutors. Come help us build the world's largest English learning marketplace and school. We're looking for a Staff Software Engineer to own the technical direction of the products we ship. You'll be a senior technical owner on a fast-moving engineering team of around 15 engineers: backend-strong, comfortable working across the stack, and accountable for taking products from design through launch. You'll work closely with product managers, designers, and engineers, and you'll set the bar for how the team builds. We're bringing AI to language learning in a way that strengthens what makes Cambly work: real tutors and real human connection. And we build AI-first: implementation is delegated to AI coding tools so engineers spend their time on the decisions, design, and review that actually shape the product. That's how you work too. Our frontend is built on Next.js, React, and TypeScript. Our backend is built with Python (Flask and FastAPI) on AWS with MongoDB. YOU WILL - Own the product platform. Lead the design and delivery of our backend systems: APIs, data models, and services, and be accountable for them working in production. - Make the hard calls. Own the judgment that shapes product work, including how we model the domain and when to build for scale and extensibility versus building quickly for fast learnings. - Ship end to end. Take products from technical design through launch, and own major initiatives across the team. - Work across the stack. Pick up frontend, mobile, and data work outside your core when a product needs it, using AI to be effective in areas where you aren't the resident expert. - Set how we build. Raise the technical bar through architecture, reviews, and good practices, and turn the AI workflows that work into practices

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