AI Engineering is one of the highest-paying and fastest-growing tech roles. Role definitions: ML Engineer focuses on model training, evaluation, and deployment infrastructure; AI Engineer typically refers to application-layer developers building with LLMs and AI APIs; Research Scientist focuses on novel model development. Salary ranges (US 2025): Junior AI Engineer $120-160K, Senior AI Engineer $180-280K, Staff/Principal $280-450K+, research scientists at top labs $400K-$1M+. Core skills needed: Python proficiency, understanding of ML fundamentals (no need to research new algorithms, but must understand how they work), experience with LLM APIs and prompt engineering, data pipeline knowledge, MLOps tools. Resume differentiators: production AI projects with measurable impact, open source contributions, writing/speaking. Learning roadmap: 1) Python + data science basics (3 months), 2) ML fundamentals via Fast.ai or Coursera (3 months), 3) LLM application development with LangChain/LlamaIndex (2 months), 4) MLOps with MLflow + cloud (2 months), 5) Build portfolio projects (ongoing). Companies hiring most: Big Tech (FAANG), AI-native startups, financial institutions, healthcare companies.