Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
AI Systems Engineering: Designing Reliable, Scalable, and Observable AI Platforms for Production

AI Systems Engineering: Designing Reliable, Scalable, and Observable AI Platforms for Production

Orion, Cipher

Paperback

Series: The AI Inference Engineering

General ComputersProgramming

ISBN13: 9798193064237
Publisher: Independently Published
Published: Aug 16 2026
Pages: 120
Weight: 0.49
Height: 0.25 Width: 7.00 Depth: 10.00
Language: English
Build AI Systems That Survive Production
Building an AI application is no longer primarily a question of connecting an application to a model API. The difficult engineering work begins when that application must operate reliably under real-world conditions.

Production AI systems must handle unpredictable model behavior, changing data, variable workloads, latency constraints, infrastructure failures, security threats, rising inference costs, evaluation challenges, and operational incidents. A prototype that works in a development environment can quickly become unreliable when exposed to real users and production traffic.

AI Systems Engineering presents a systems-oriented approach to designing, deploying, operating, and scaling modern artificial intelligence platforms.

Rather than focusing exclusively on prompts or individual models, this book examines the complete engineering environment surrounding AI workloads from data and knowledge infrastructure to model serving, application runtimes, evaluation pipelines, observability, reliability, security, and distributed production architecture.

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