Synchronous HTTP request-response patterns collapse under production LLM workloads. This article provides a principal-architect-level blueprint for building async AI systems using message queues, specialized worker fleets, and event-driven push delivery — covering everything from queue topology and GPU-aware scaling through cost engineering, failure resilience, and the operational tradeoffs that only emerge at scale.