Prepare for an AI platform engineering interview that asks about RAG, indexing, database choices, evaluators, stream data handling, OOP principles, binary search, algorithm constraints beyond time and space, encapsulation versus abstraction, cohesion and coupling, ETL, SOLID principles, linked lists, and reversing a linked list. ```hint Hint 1 Start by naming the core entities, constraints, and success criteria. ``` ```hint Hint 2 Make the trade-offs explicit before going deep on implementation details. ``` ### Constraints & Assumptions - The prompt is a fundamentals screen with many short topics. - Answers should be concise but connected to practical engineering choices. - For coding basics, explain both the algorithm and why it is appropriate. - For RAG topics, include evaluation and data handling, not only definitions. ### Clarifying Questions to Ask - Is the role more backend platform or applied AI? - What data volume and freshness does indexing require? - Which database options are available? - Should stream data be processed exactly once or at least once? - Which programming language should pseudocode use? ### What a Strong Answer Covers ```premium-lock What a Strong Answer Covers ``` ### Follow-up Questions - How would you evaluate a RAG answer? - When would you choose a vector database over a search index? - What non-complexity constraints matter in algorithm evaluation? - How would you reverse a linked list iteratively and recursively?