Generative AI Engineering with MLOps: Deploying, Scaling, and Monitoring LLMs and Foundation Models

Deploying, Scaling, and Monitoring LLMs and Foundation Models to Build Production-Ready Chatbots, Agents, and Diffusion Models

Generative AI Engineering with MLOps is your complete, practical roadmap to deploying, scaling, and monitoring modern AI systems in real-world environments. Designed for engineers, data scientists, and forward-thinking leaders, this book bridges the gap between machine learning theory and practical MLOps execution—showing you how to move from prototype to production without compromise.

Inside, you’ll discover how to:

• Build reliable retrieval-augmented generation (RAG) systems that deliver grounded answers

• Fine-tune large language models with LoRA/QLoRA for cost-efficient adaptation

• Deploy models at scale with vLLM, Ray Serve, Triton, and KServe

• Design safe and efficient AI agents with tool orchestration, guardrails, and HITL strategies

• Operationalize diffusion models with caching, quotas, and policy enforcement

• Implement observability, drift detection, and cost monitoring to ensure production stability

Every chapter includes hands-on labs with complete, working Python code explained step by step—so you don’t just read about concepts, you build and run them. By the end, you’ll have the skills and confidence to design and manage AI systems that are both powerful and trustworthy.

Jacobs V. Bradley is a seasoned practitioner and educator in MLOps, Generative AI, and scalable cloud systems. With years of experience bridging research, engineering, and production deployment, Bradley brings a unique ability to simplify complex technologies without losing depth. His work emphasizes practical engineering, credibility, and time-tested workflows—ensuring readers gain actionable expertise that aligns with today’s fast-moving AI landscape.

Whether you’re a professional upgrading your skills, a student stepping into AI engineering, or a business leader seeking to deploy cutting-edge systems, this book offers the clarity, practicality, and credibility you need to succeed.

Unlock the tools of the next decade. Step into the world of Applied Generative AI Engineering and deliver AI solutions that truly work in production.