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Engineering & Product

Backend & Data Engineer

TypeScript · Convex

Founding · equity-first Remote · any timezone

Own the state the training engine reasons over — readiness, load, history — and the guarantees that keep it correct.

What you would own

  • Model and evolve the training state in Convex without breaking athletes mid-block
  • Keep the readiness and load computations deterministic, traceable, and covered by tests
  • Build the export and delete paths that the Privacy Policy already promises
  • Instrument the backend so a wrong session can be traced to the rule that produced it

What you bring

  • Strong TypeScript and a track record with a reactive or document database
  • Discipline about migrations on live user data
  • A bias toward explainable logic over clever logic

Nice to have

  • Convex specifically
  • Time-series or training-load modelling
  • GDPR-shaped data work

Founding · equity-first. Pre-revenue. Equity or profit-share, agreed in writing before you start.

What happens next

  1. 01

    Every application is read by a person here — no tracker, no keyword filter, no auto-reject.

  2. 02

    First call is 30 minutes on data modelling decisions you have regretted and what you did about them.

  3. 03

    The technical step is a schema-and-migration problem from the real codebase, timeboxed.

Worth preparing. Think of one migration you ran against live user data. What you did to make it safe is most of what we will talk about.

Apply

0 / 4000 · 40 minimum

One application per role per email — sending again updates what we hold rather than creating a duplicate. No trackers. Your details are never sold or shared.

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