ML observability and agent engineering at DICK’S Sporting Goods
An event-driven observability platform on Databricks designed for reusable model onboarding, plus engineering contributions across the client’s customer-facing agentic platform.
- 10× faster model onboarding. DICK’S Sporting Goods.
Context & problem
DICK’S Sporting Goods needed a shared observability path for a growing ML suite. Onboarding a new model into monitoring was slow, bespoke work repeated across use cases. I delivered the platform through Tredence, then contributed engineering across the client’s customer-facing agentic platform.
What I built
An event-driven observability platform on Databricks, designed to be reusable across business ML use cases without rebuilding the monitoring path each time. When the client launched its customer-facing agentic AI experience, I also contributed across the agent stack, from observability through platform engineering.
Measured result
Model onboarding became 10× faster.
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