Building AI applications is no longer just about selecting the best model. Developers must design systems that combine models, tools, memory, orchestration, evaluation, and observability into reliable, production-ready software. This keynote explores the architectural patterns emerging across modern AI engineering and the technical decisions required to build AI systems that are scalable, resilient, and ready for real-world deployment.