Intelligent Systems Engineering: Empowering the Node.js Backend with Natural Language Processing LLM

Your Node.js backend can do far more than send requests to an LLM. It can become the foundation of a scalable, secure, intelligent AI application. Intelligent Systems Engineering explores how Node.js developers can move beyond basic API integrations and engineer production-ready applications powered by large language models and modern natural language processing. From connecting multiple LLM providers to building RAG pipelines, managing conversational memory, orchestrating AI agents, and controlling inference costs, this book focuses on the engineering decisions that matter when AI applications move from prototype to production. Inside, you'll explore: - OpenAI, Anthropic, and Google AI integrations with Node.js- Prompt engineering, structured outputs, and prompt-injection defenses- RAG pipelines, embeddings, vector databases, and semantic search- Redis-powered conversational memory and context management- Agentic workflows, function calling, MCP, and human-in-the-loop patterns- Semantic caching, batching, rate limiting, and token-cost optimization- PII protection, audit logging, privacy, and enterprise AI security- LLM testing, hallucination mitigation, RAG evaluation, and prompt benchmarking- High-concurrency architectures using WebSockets, SSE, containers, and serverless deploymentsWhether you're a Node.js developer entering AI engineering or an engineer building production LLM applications, this guide connects JavaScript backend development with the practical realities of modern generative AI. Build smarter backends. Engineer more reliable LLM applications. Bring intelligent systems to life with Node.js.