VLink interview questions

Core System: How do you design an end-to-end Video RAG system using an MCP server for an Agentic LLM to query multi-modal video indices? Security & Protocol: How do you build a secure MCP architecture connecting a cloud LLM to an isolated on-premise video analytics cluster with dynamic tool discovery? Multimodal Alignment: How do you chunk and embed synced video, audio, and OCR data to return exact timestamps instead of broad clips? Agentic Workflows: How do you structure an Agent's ReAct loop to chain multiple MCP tools for complex queries without looping infinitely? Latency: How do you handle slow, async tool execution (e.g., YOLO) while keeping the LLM chat responsive? Token Economics: How do you optimize context windows using reranking or caching for long-form video analysis? Guardrails: What validation loops mitigate LLM hallucinations against raw video metadata? Scaling: Where are the bottlenecks when scaling to 10k users, and how do you optimize compute costs? Coding: Write an O(1) space, case-insensitive palindrome checker in Python that ignores non-alphanumeric characters.