This course develops the engineering capabilities required to train, deploy, scale, secure, monitor, and operate production AI systems. Learners study distributed training, GPU and accelerator systems, model serving, high-performance inference, containers, orchestration, MLOps, LLMOps, observability, reliability, security, cost engineering, capacity planning, and governance. The course treats AI as critical infrastructure rather than a standalone software feature.