AI Engineering Lead, Product Analytics

Summary

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. 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. This is a hands‑on role; you build, and you keep our builders moving faster.

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. 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 prototyped and extending it into something more capable and broadly useful. Stay close enough to the build to keep your judgment about the tooling sharp.
• Own Evaluations and the Definition of Done: Define what production means for the team’s AI work and own the evaluation standard that holds it there. Build the tooling that lets analysts run evaluations themselves, and bring the team’s evaluation practice up over time.
• Close Pipeline Gaps: Find the breaks between collecting the right data and shipping the self‑service AI tooling product managers use to understand user behavior in our products. Diagnose where data, context, or infrastructure is missing, drive the work to close those gaps, and advocate to get the right sources into the data lake.
• Set the Build Standards: Own how the team creates and manages its build artifacts: repository conventions, context files, documentation that makes agents reliable. Keep these changes cheap and fast to make so the standards speed builders up. Propose, with conviction, which work streams should move fully to AI first, and sequence them so early wins build credibility.
• Make Builders Better: Bring analysts along by teaching the infrastructure they use; the person who sets the eval standard and the repository conventions is the one who shows people how to work with them. Keep the upskilling tied to real deliverables and to tooling people already touch, so the practice sticks.
• Governance and Compliance: Navigate TR’s AI governance landscape on the team’s behalf. Help analysts build to TR standards, support compliance where agents touch sensitive data and decisions, and keep governance workable so it does not block shipping.
• Scale Adoption Across the Team: Make the team’s tools findable and usable by someone who has no direct relationship with whoever built them. Keep the registry current, manage how tools move from prototype to shared and depended‑on, and catch drift before it reaches stakeholders.
• Interface Outward: Represent the team in TR‑wide AI conversations, connect with AI leaders in other product groups, and keep the link to TR’s AI transformation program active. Manage the cross‑team dependencies the work runs on, including data lake access and platform infrastructure.
• Keep Production Agents Healthy: Establish how the team watches its own agents once they run in production, so breakage and quality drift get caught early. Give every production tool a clear owner and a monitored definition of done.

This role suits someone who builds and who has run programs that scale across a team. You are a strong engineer who works alongside other builders, shaping infrastructure with them so they trust it and use it, and you have driven…