This article presents a comprehensive roadmap for aspiring LLM engineers, outlining essential knowledge and skills to master. It divides the learning journey into foundational topics, LLM fundamentals, vector databases, RAG basics, deployment strategies, and advanced techniques. The roadmap emphasizes hands-on experience and practical applications, including LLM optimization and ethical considerations. It aims to help learners progress from basic concepts to advanced LLM engineering skills, preparing them for real-world challenges in AI and machine learning.