Das ist der Job
This is a hands‑on role; you build, and you keep our builders moving faster.
Darum lohnt es sich
We are seeking an AI Engineering Lead to own that layer across a team of roughly 35 analysts supporting 60+ products. You will build the shared repositories, standards, context, and evaluation tooling our analysts depend on, and you will define what production means for the team's AI work.
You will also build agents yourself, often expanding what others have prototyped into something the whole team can use.
About The Role
As AI Engineering Lead, Product Analytics, you will be responsible for:
Own the Shared Infrastructure: Build and maintain the shared assets our analysts build on: the team's Git repositories, reusable components, context and data‑access standards, and a registry of what exists and who owns it.
Take what individual builders make locally and generalize it so the whole team can use it. Product Analytics is building self‑service tools and operating AI agents that influence product development; agents that monitor product health, surface anomalies, analyze user behavior, and produce the insights product leaders rely on.
As more analysts build, the work needs someone to scale agentic solutions and own the shared infrastructure underneath it. Build this as self‑service so analysts move forward by using the tooling, not by waiting on you. Build Agents: Build production AI agents yourself, frequently by picking up a tool another analyst prototype
