GenAI System Design Interview Mastery: A Complete Guide to Enterprise LLMs, RAG, Agentic AI, Production Architecture, Evaluation, Security, Reliability & AI FinOps
Language: English
Published by Independently published, 2026
- Softcover
- New

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- Title
- GenAI System Design Interview Mastery: A Complete Guide to Enterprise LLMs, RAG, Agentic AI, Production Architecture, Evaluation, Security, Reliability & AI FinOps
- Author
- Kumar, Dr. Sanjay Nakharu Prasad
- Publisher
- Independently published
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798165230967
Master Enterprise Generative AI Architecture and Ace Your AI System Design Interviews!
GenAI System Design Interview Mastery is a comprehensive, practical guide to designing scalable, secure, reliable, and cost-efficient Generative AI systems. Written for AI Engineers, Solution Architects, Technical Product Managers, Forward Deployed Engineers, and senior technology professionals, this book bridges the gap between foundational AI concepts and real-world enterprise architecture.
From Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to Agentic AI, multi-agent orchestration, model serving, and production deployment, this book explores the essential principles, architectural patterns, engineering trade-offs, and interview strategies required to build enterprise-grade AI solutions.
What You'll Learn:
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GenAI System Design: API gateways, load balancing, caching, scalability, asynchronous processing, and distributed architectures.
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LLM Architecture: Model serving, inference optimization, intelligent routing, token management, and deployment strategies.
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RAG Engineering: Embeddings, vector databases, hybrid search, reranking, context engineering, and grounded generation.
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Agentic AI: AI agents, tool integration, workflow orchestration, memory management, and multi-agent architectures.
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Production AI Engineering: Observability, evaluation frameworks, guardrails, security, resilience, and responsible AI governance.
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AI Cost Optimization: AI FinOps, caching strategies, model selection, infrastructure efficiency, and cost-performance trade-offs.
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Enterprise Case Studies: Practical architecture scenarios involving banking, healthcare, insurance, public-sector systems, and customer support.
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Interview Preparation: Technical questions with detailed explanations, architecture exercises, design decisions, and practical interview frameworks.
Who Should Read This Book?
Whether you're preparing for a Senior AI Engineer, AI Architect, Principal Engineer, AI Product Manager, or Forward Deployed Engineer interview—or designing production AI systems—this book provides the technical foundation and structured problem-solving approach needed to succeed.
Go beyond prompts and prototypes. Learn to architect, evaluate, secure, and scale Generative AI systems for the real world.
Build stronger AI architecture skills. Make better engineering decisions. Prepare confidently for your next technical interview.
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