Applied AI Engineer: Build, Evaluate, and Operate Production LLM

Large language models power a growing range of products, but moving from a working prototype to a reliable production system takes more than good prompts. Applied AI engineering brings model selection, retrieval, agents, evaluation, and deployment together so applications stay accurate, affordable, and safe under real traffic. You’ll start with LLM fundamentals and model selection, then build RAG pipelines with hybrid search and multi-step reasoning agents. Next, you’ll evaluate and fine-tune models, and deploy pipelines as API microservices with caching and CI/CD tests that catch hallucinations. You’ll then combine speech, vision, and image generation into one multimodal pipeline. You’ll finish by securing systems against prompt injection, protecting PII, testing for bias, and adding layered guardrails and monitoring. By the end, you’ll be able to build, evaluate, and operate production-ready LLM applications that stay reliable, cost-efficient, and secure.