Java AI Engineer – Volume 4: Enterprise AI Engineering

From AI Prototypes to Production-Ready Enterprise Systems.

20 Chapters | Production AI Engineering | PDF + EPUB + Source Code

Building an AI-powered application is one thing. Running it reliably in a high-throughput enterprise environment is another.

What happens when an AI provider goes down? How do you control unpredictable token costs, protect sensitive information, prevent prompt injection, and investigate failures across complex LLM workflows?

In this volume, you'll learn the engineering practices required to deploy and operate AI applications in production. Explore the 12 AI failure modes, cost guardrails, prompt injection prevention, PII redaction, distributed tracing, observability, provider failures, and production incident response.

Move beyond working AI prototypes and learn how to engineer AI systems that are reliable, secure, observable, and ready for enterprise workloads.

WHAT YOU’LL BUILD & MASTER

1. Handle Enterprise AI Risks

• Understand and diagnose 12 AI failure modes.
• Identify and handle prompt injection threats.
• Protect sensitive information through PII redaction.
• Handle AI provider failures and service disruptions.

2. Build Production Guardrails

• Enforce cost controls and token budgets.
• Monitor token consumption and AI usage.
• Implement observability for AI-powered applications.
• Build distributed tracing across LLM call chains.

3. Prepare AI Applications for Production

• Understand deployment challenges in enterprise AI.
• Handle service degradation and provider disruptions.
• Prepare for production incidents.
• Apply engineering practices for reliable AI operations.

WHAT’S INSIDE THIS VOLUME?

• Enterprise AI engineering
• 12 AI failure modes
• Prompt injection prevention
• PII protection and redaction
• AI provider failure handling
• Cost guardrails and token budgets
• Token usage monitoring
• Observability for LLM applications
• Distributed tracing across LLM call chains
• Production deployment
• Service degradation strategies
• Production incident response

WHY SHOULD JAVA DEVELOPERS READ THIS BOOK?

• Building an AI feature is only the beginning. Enterprise engineering requires much more than connecting an application to an LLM.
• Java developers already understand production systems, APIs, distributed services, and reliability. This volume extends that engineering mindset to AI applications.
• Learn how to identify risks, control costs, protect sensitive data, trace complex AI workflows, and prepare applications for real-world production challenges.
• Whether you're a Java developer moving into AI engineering or an experienced Spring Boot engineer building enterprise AI solutions, this volume helps you understand what it takes to operate AI beyond the prototype stage.

PRODUCT DETAILS

Series: Java AI Engineer

Publisher: Java Puzzle Publication

Volume: 04 – Enterprise AI Engineering

Category: Production

Chapters: 20

Format: PDF + EPUB

Source Code: Accompanying source code included

Delivery: Instant digital download

Edition: DRM-Free

Updates: Lifetime updates

BUILD AI THAT IS READY FOR THE REAL WORLD.

Don't stop at making AI work. Learn how to make it reliable, secure, observable, and production-ready.

From Prototype to Production. From Possibility to Reliability.

Continue your Java AI engineering journey with Volume 4 of the Java AI Engineer series by Java Puzzle Publication.

Learn. Build. Solve. Innovate.