Architecting AI Software Systems

Architecting AI Software Systems: Crafting Robust and Scalable AI Systems for Modern Software Development

Bridge the gap between experimental models and industrial-strength intelligence. Architecting AI Software Systems provides a definitive, engineering-first roadmap to the structural core of modern AI. Learn how to move beyond basic scripts to high-performance, production-ready ecosystems—bridging the gap between a standalone Large Language Model (LLM) and a scalable enterprise solution—ensuring your digital products are resilient, maintainable, and future-proof in the 2026 landscape.

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What You Will Learn:

Foundations of AI Architecture: Master the core principles of designing systems that effectively integrate machine learning models into traditional software stacks.

Scalable AI Infrastructure: Step-by-step guidance on utilizing microservices, containers, and serverless computing to handle intensive AI workloads at scale.

AIOps & CI/CD for ML: Discover how to build automated pipelines for model deployment, monitoring, and continuous retraining to prevent performance drift.

Designing for Reliability & Security: Learn advanced techniques for implementing robust error handling, data privacy protocols, and "Zero Trust" security within AI-driven environments.

Who This Book is For: This professional-grade guide is essential for Software Architects, Senior Developers, and AI Engineers. It is an invaluable resource for any technical lead—including those building security-focused graduation projects like Smart Guard—aiming to master the structural integrity and scalability required for mission-critical intelligent applications.

Product Details:

Format: Digital PDF Download

Authors: Richard D. Avila; Imran Ahmad

Publisher: Packt Publishing

ISBN-13: 9781804615973

ISBN-10: 1804615978