I recently interviewed for the AI Engineer – NLP/LLM Data Product role at Athenahealth. Interview Process: The first round was scheduled, but the interviewer didn’t show up. The second attempt went ahead as planned with two panelists. The session was framed as a technical discussion. I was asked to explain one of my recent projects (a Conversational Q&A platform) in detail. The panel focused heavily on technical flow and expected me to write function-level code for each step, explain the logic, input parameters, and purpose. We then discussed deployment – I was asked to explain API structure, input/output JSON formats, and also write a Dockerfile outline. There was also a question around system behavior at scale, where I discussed queues and autoscaling based on my experience. In hindsight, they were looking for rate-limiting techniques, though it wasn’t made clear during the discussion. Feedback Experience: I was later told that I was not selected due to “lack of microservices knowledge.” Surprisingly, not even a single question was asked related to microservices architecture during the entire session. This felt a bit inconsistent with the actual interview content and expectations.