A quick phone call lead to an in person interview. There weren't any technical questions asked, just questions about what you could do. This included a sit down with a PM and eventually the floor manager. They ultimately wanted more experience than I had.

I went through a multi-round interview process for a Senior Data Engineer role on the AI Products & Platform team. The final round involved a technical case study focused on real-time data pipelines, ML model operationalization, and activation into customer-facing systems (e.g., IVR/CCAI). The discussion was practical and closer to real production scenarios than purely theoretical interviews, which I appreciated. The panel was professional and engaged, and the questions covered system design tradeoffs, latency, failure handling, monitoring, and cost considerations. The format allowed for explaining architectural reasoning rather than just listing tools. Advice to candidates: Come prepared to discuss real-world tradeoffs, operational concerns, and how ML outputs are safely activated in production systems. Be clear and concise in your design and reasoning.