Member of Technical Staff

We're building an AI system that generates multimodal learning content — text, images, voice — and closes the loop with a platform that adapts to each learner and surfaces insight back to teachers. Content is produced, reviewed, consumed, scored, and fed into the next recommendation. Nobody has walked that full loop yet. We are.

The architecture is built and running at a working prototype. The codebase spans Go backends, React frontends, and an LLM agent layer that ties them together. We need engineers who are fluent across that full span — not because we can't afford specialists, but because the interesting problems live at the seams. If you can't write a React component or have never touched a database, this isn't the role. We're not hiring boxes; we're hiring people who chose breadth on purpose.

One day you're writing a Go handler in a workflow engine. The next you're building a React component for the end-user app. The day after, you're tuning a Redis stream consumer, wiring up an LLM call with telemetry, or making cross-content visual consistency a real engineering problem instead of a prompt-tuning lottery. You'll ship the AI companion chat experience, the content review pipeline, the analytics layer, and the observability that keeps the whole thing honest.

We're a small team in Guangzhou, and we hire people who build things that matter. We offer equity to every role, a 13-month salary, no timesheets, and the freedom to use whatever tools make you fast. If this is the kind of work that excites you, send your resume. We'll reach out if there's a strong fit.