Production -Ready Agentic AI for Data Engineers: Building Safe, Observable, and Reliable AI Agents on Modern Data Platforms

By Ravi Kiran

Production-Ready Agentic AI for Data Engineers
Build Enterprise AI Agents with LangGraph, MCP, A2A, RAG, Databricks, and Production Best Practices

Artificial Intelligence is rapidly evolving from simple chatbots to autonomous, intelligent agents capable of planning, reasoning, collaborating, and executing complex workflows. While many books focus on AI concepts or basic prototypes, very few teach you how to build production-ready Agentic AI systems that are secure, scalable, observable, and enterprise-ready.

This book bridges that gap.

Production-Ready Agentic AI for Data Engineers is a practical, hands-on guide designed for data engineers, AI engineers, machine learning engineers, software developers, cloud architects, and technical professionals who want to design, build, deploy, and operate enterprise-grade AI agent systems.

Rather than stopping at proof-of-concept demos, you'll learn the engineering practices required to move Agentic AI into production with confidence.

Inside this book, you'll learn how to:

Understand Agentic AI architecture and multi-agent systems

Build intelligent AI agents using LangGraph

Design planning, reasoning, and memory workflows

Implement Retrieval-Augmented Generation (RAG) pipelines

Integrate Model Context Protocol (MCP) into agent ecosystems

Enable Agent-to-Agent (A2A) communication patterns

Build secure enterprise AI applications

Deploy scalable AI workloads on Databricks

Implement observability, tracing, evaluation, and monitoring

Apply guardrails to reduce hallucinations and prompt injection risks

Manage long-term memory, semantic caching, and vector databases

Orchestrate AI workflows with modern engineering patterns

Optimize performance, latency, and operational costs

Design production-ready APIs and deployment architectures

Apply governance, security, compliance, and responsible AI practices

Topics Covered

Agentic AI Fundamentals

Enterprise AI Architecture

LangGraph

Multi-Agent Systems

MCP (Model Context Protocol)

Agent-to-Agent (A2A) Communication

Retrieval-Augmented Generation (RAG)

Vector Databases

Semantic Search

Embeddings

Memory Architectures

Tool Calling

Function Calling

Databricks AI Platform

AI Workflows

AI Deployment

Production APIs

Evaluation Frameworks

AI Observability

Logging and Tracing

Security Best Practices

Prompt Engineering

Prompt Injection Defense

Guardrails

Human-in-the-Loop Systems

Responsible AI

Performance Optimization

Scalability

Cloud Deployment

Production Monitoring

Who This Book Is For

This book is ideal for:

Data Engineers

AI Engineers

Machine Learning Engineers

Software Engineers

Data Scientists

Cloud Engineers

MLOps Engineers

Platform Engineers

Solutions Architects

Technical Leads

Engineering Managers

Enterprise AI Teams

Students and professionals transitioning into AI engineering

• Format: Paperback
• Language: English
• ISBN: B0H9RHYN66
• ISBN13: 9798188295417
• Release Date: July 2026
• Publisher: Independently Published
• Length: 412 Pages
• Weight: 1.09 lbs.
• Dimensions: 1.0" x 6.0" x 9.0"