Anthropic System Design interview questions focus on practical, safety-aware architecture for large-scale AI systems. Expect prompts that blend classic distributed-systems concerns—scalability, availability, consistency, caching, and monitoring—with Anthropic-specific topics like LLM inference pipelines, moderation/safety layers, token and cost management, and GPU scheduling. Interviewers evaluate your ability to break problems into components, define clear requirements and SLAs, reason about trade-offs, and surface failure modes and mitigation plans. For interview preparation, practice end-to-end designs that explicitly call out data flow, interfaces, storage choices, and operational concerns (latency, throughput, observability). Prepare to discuss LLM-tailored constraints such as prompt engineering, batching versus real-time inference, and safe-fail patterns. Use a structured approach: clarify goals and constraints, sketch components and APIs, justify technology and scaling choices, and describe testing and rollback strategies. Be ready to dive into one area in depth when probed, and to explain trade-offs and safety considerations clearly and concisely.