System Design AI Interview PDF

Enterprise RAG interviews test system design at scale: ACL-aware retrieval, audit logging, and ingestion pipelines for millions of documents. This is a staff-level question appearing at Microsoft, Salesforce, and Fortune 500 AI teams. Walk through a complete architecture with security boundaries and operational concerns.

Multi-agent orchestration is a senior/staff-level system design question gaining traction at Google DeepMind and Microsoft. Learn the supervisor pattern, shared state management, and how to avoid the 'too many agents' anti-pattern that sinks most candidate answers.

500M vectors at sub-100ms p99 is a staff-level vector search design question from Uber, Airbnb, and large-scale ML platform teams. Learn sharding strategies, index tuning, and the operational trade-offs that separate senior from principal engineers.

A production AI coding agent typically includes:

This is an enterprise platform design question spanning agents, MCP, governance, and observability.

**Behavior** More deliberation tokens internally — improved accuracy on complex code/math.

**Model behavior** o-series and GPT-4.1 emphasize extended internal reasoning before answer — improved reliability on complex tasks, not always needed for chat.

**Graph structure** draft → auto_checks → legal_subgraph → manager_subgraph → publish; reject edges loop to draft with comments in state.

**State schema** ticket_id, customer_tier, messages, retrieved_docs, proposed_actions, sentiment, escalation_reason, resolution_code.

Company-based system design: sharded ANN, metadata pre-filtering, query routing, reranking, and latency SLOs at marketplace scale.

Horizontal scaling patterns: hash sharding, semantic partitions, routing embeddings, and merge/rerank at query time.

Company-based system design prompt for tool-using assistants with scope limits, confirmation gates, and structured tool policies.

Hard AI Agents interview question on google interview: multi-agent search system — architecture, trade-offs, eval, and production patterns.

Hard AI Agents interview question on customer support agent system design — architecture, trade-offs, eval, and production patterns.

Hard RAG interview question on openai interview: customer support rag — architecture, trade-offs, eval, and production patterns.

Hard OpenAI company question — chat product system design with safety stack, eval gates, streaming, and grounding.