Generative AI Engineer Official Body of Knowledge

Free Download Generative AI Engineer: Official Body of Knowledge
English | December 5, 2025 | ASIN: B0G56H678Z | 740 pages | Epub | 481.32 KB
Generative AI has moved from lab demos to the center of real products, internal tools, and whole business workflows. Every organization now needs people who can do more than "chat with a model"-they need engineers who can design, ship, and govern production-grade LLM systems. This book is written to make you that person. Developed as the official reference for the GreenTech Academy Generative AI Engineer certification, this Body of Knowledge walks you end-to-end through modern generative AI practice. You'll build a grounded understanding of AI fundamentals, then layer on the skills that matter most in the field today: prompt engineering, retrieval-augmented generation (RAG), agents and tool use, safety and governance, evaluation, and real-world integration patterns. Each module connects theory to architecture diagrams, small-business scenarios, and exam-style thinking so you can use what you learn on the job and on test day. Unlike books that focus on a single library or model, Generative AI Engineer teaches you how to think in systems. You'll see how prompts become versioned interfaces, how RAG pipelines turn static documents into living knowledge, how agents coordinate tools without losing safety, and how LLM services plug into existing APIs, SaaS platforms, and data stacks. Throughout, you'll learn to treat safety, cost, and reliability as first-class design requirements-not afterthoughts. The final chapters map this skill set directly to the job market, outlining the roles and salary bands emerging around generative AI and showing how this certification fits into that landscape. Inside, you'll learn how to: Build a practical foundation in AI history, machine learning, deep learning, and LLM fundamentals. Design prompts, roles, and structured outputs that behave predictably in production. Architect LLM integrations with service layers, gateways, streaming, and reliability patterns. Implement RAG systems with thoughtful chunking, embeddings, metadata, and corpus governance. Design and constrain agents that call tools, manage workflows, and keep humans in the loop. Evaluate generative systems with test sets, metrics, and safety checks that go beyond "it looks good." Translate these skills into real roles: Generative AI Engineer, LLM Engineer, RAG Engineer, AI Solutions Architect, and more. Perfect for: Software and cloud engineers adding generative AI to their toolkit. Data and ML practitioners moving from models to full LLM applications. Architects, technical leads, and IT professionals defining AI strategy. Career-changers and students preparing for the GreenTech Academy certification and modern AI roles. If you want a clear, opinionated roadmap from fundamentals to production-ready systems-and a book you can keep on your desk as both a study guide and a day-to-day reference- Generative AI Engineer: Official Body of Knowledge is your blueprint.