LLM Engineer course launches June 4 with production stack focus
AI Talent Hub and GIGASCHOOL are offering a six-month online program starting June 4 that teaches transformer architecture, agent safety, LLMOps, and production deployment to backend and ML engineers. Early-bird pricing ends Thursday.
LLM engineering has become one of the fastest career accelerators for backend, ML, and DevOps engineers seeking to move up in scope and compensation.
AI Talent Hub and GIGASCHOOL are launching an updated "LLM Engineer" course on June 4, running six months as live online seminars. The curriculum covers the production stack companies now expect: transformer internals, retrieval-augmented generation with reranking and evaluation, agent orchestration, LLMOps tooling including vLLM and SGLang, and observability. Students work through the full lifecycle of an LLM product—fine-tuning via QLoRA and PEFT, deploying a production service under load, monitoring latency and cost, and assessing output quality at scale.
The program also includes AI red teaming and agent-system security, skills that remain rare but increasingly critical as companies ship agentic workflows to production. Students build a portfolio on GitHub: a RAG system over a corporate knowledge base, a multi-agent pipeline, a domain-adapted LLM or encoder, a Dockerized production service, and a standard security audit report.
Early-bird pricing ends Thursday, with rates rising after that. The course targets engineers already working in adjacent roles who want to add LLM infrastructure to their toolkit without switching careers entirely.