Deep dive into resume projects and tools used, followed by system design discussions focused on LLM architectures, scalability, and deployment considerations. Demonstrated strong knowledge of Retrieval-Augmented Generation (RAG), including indexing strategies, retrieval mechanisms, embeddings, evaluation metrics, and complete end-to-end functionality.