In the rapidly evolving landscape of generative AI and cloud computing, moving from a prototype to a production-ready application requires more than just a basic understanding of APIs-it demands a deep mastery of infrastructure, orchestration, and ethical governance. Azure AI Engineering: Architecting Scalable Intelligence is the definitive technical blueprint for developers, architects, and data scientists looking to leverage the full power of the Microsoft Azure AI ecosystem.This high-level guide transcends introductory concepts, diving straight into the complexities of building enterprise-grade intelligent systems. From optimizing Azure OpenAI Service for low-latency responses to implementing sophisticated RAG (Retrieval-Augmented Generation) architectures using Azure AI Search, this book provides the rigorous technical depth required to solve real-world engineering challenges.Inside, you will explore the unified capabilities of Azure AI Studio, the robust automation of Azure Machine Learning, and the specialized power of Azure AI Services (formerly Cognitive Services). Whether you are fine-tuning models with LoRA, implementing complex LLMOps pipelines, or securing data within a Private Link environment, this book offers the precise, step-by-step technical guidance necessary to succeed.Key topics include: - Advanced Prompt Engineering and Semantic Kernel integration.- Architecting high-performance Vector Databases and Hybrid Search.- Fine-tuning Large Language Models (LLMs) and Model Distillation.- Automating MLOps and LLMOps for continuous integration and deployment.- Implementing Content Safety and Responsible AI frameworks.Take command of the future of AI development. Scroll up and secure your copy of "Azure AI Engineering" today to begin building the next generation of intelligent, cloud-native applications.