QA Engineer (AI + backend)

Engagement: We are partnering with a US-based health-tech company on the takeover of a production AI-powered mobile coaching platform. Real users, real production, real releases — not a greenfield project. Role summary: Own quality on the two hardest surfaces of a production AI coaching platform: the LLM agents that answer differently every run, and the API layer everything else depends on.

As AI & Backend QA Engineer you own the quality of what the model says and what the APIs return. On the AI side that means building the evaluation practice: golden sets, quality metrics, and regression detection that catch a degraded answer before a user does. On the backend side it means API test suites and consumer-driven contract testing with Pact — agreed with the client's US engineering team as a standing requirement for this role, not an optional technique.

The defining skill is localization: when an answer is wrong, you can tell whether the problem sits in the model, in the service code, or in the input data — and you bring the evidence, not a guess. What you'll be testing: AI core — a Python service with LangGraph agents producing streaming, non-deterministic coaching responses; this role's primary surface Backend APIs — a NestJS REST gateway behind Auth0, plus the services behind it Mobile app — React Native, shipping to iOS and Android app stores; AI features surface directly in the app that members use Data layer — MongoDB, Redis, and Postgres behind the services Process — Agile