RAG Interview Questions: Complete Guide for AI Engineers

Description

Master Retrieval-Augmented Generation (RAG) with this comprehensive guide covering 20 essential interview questions. Learn everything from RAG fundamentals and architecture to advanced techniques like multi-hop reasoning and agentic RAG. In this video, you'll learn: • What is RAG and why it's crucial for reducing LLM hallucinations • Vector embeddings and semantic search fundamentals • Document chunking strategies (sentence-level, paragraph-level, fixed-size, overlapping, semantic) • Reranking with cross-encoders for improved retrieval accuracy • Query optimization techniques (rewriting, multi-query, multi-hop) • Agentic RAG with autonomous decision-making • Complete implementation stack (embedding models, vector databases, LLMs, frameworks) • Evaluation metrics (Precision@K, Recall@K, MAP, nDCG) • Common challenges and practical solutions • Production best practices and debugging strategies Perfect for AI/ML engineers preparing for interviews or building production RAG systems. Each concept is explained with clear visualizations and real-world examples. Topics covered: RAG architecture, embeddings, chunking, reranking, query rewriting, multi-hop RAG, agentic RAG, vector databases, FAISS, Pinecone, Weaviate, Chroma, LangChain, LlamaIndex, evaluation metrics, production deployment.