AI Engineer Interview Preparation

Description

Prepare for AI engineering interviews by learning how real LLM applications are built, evaluated, secured, and deployed.

This book takes you from the fundamentals of large language models to production-ready retrieval-augmented generation (RAG) systems and safe AI agents. Every major topic is explained in plain English, then reinforced with working code, original diagrams, and interview questions with detailed answers.

What’s inside:
• 41 chapters in 8 parts, from AI and math fundamentals to system design
• 522 original interview questions with model answers, from beginner to senior level
• How LLMs work: transformers, attention, tokens, context windows, and sampling
• Prompt engineering, LLM API integration, structured outputs, and tool calling
• Embeddings, semantic and hybrid search, BM25, and vector databases
• RAG end to end: ingestion, chunking, retrieval, reranking, citations, and evaluation
• AI agents: tool safety, memory, planning, multi-agent systems, and the Model Context Protocol (MCP)
• Evaluation, hallucination reduction, AI security, prompt injection defense, and data privacy
• Production skills: APIs, observability, deployment, scaling, and cost control
• Seven complete AI system design exercises with architecture diagrams
• Two end-to-end projects (a RAG application and a safe AI agent), 12 coding challenges, and mock interviews for four experience levels
• A 30-day study plan and final revision checklists

Practical and honest:
All code examples are original, written in Python, and tested. They run offline with mock components, so you can learn without paid API keys. The book clearly explains what each example demonstrates and where real production systems need more.

Who this book is for:
• Software developers moving into AI engineering
• Backend and full-stack developers building LLM features
• Engineers preparing for AI engineer, LLM engineer, or RAG engineer interviews
• Mid-level and senior engineers preparing for AI system design rounds

Whether you are preparing for your first AI engineering interview or an architecture round, this book helps you understand the concepts, explain trade-offs clearly, and build systems you can discuss with confidence.

Note: AI tools, models, APIs, and prices change frequently. Always verify current documentation before building production systems.