Want to become an AI Engineer in 2026? Don’t start with random AI tutorials. Follow this order: 1. Software Engineering Fundamentals Learn Python, APIs, SQL, Git, testing, debugging, Docker, cloud, authentication, logging, and deployment. 2. AI Systems Understand tokens, context windows, embeddings, retrieval, tool calling, structured outputs, model selection, latency, cost, and when you actually need an agent. 3. AI Evals Learn how to test AI systems properly. Build test sets, measure task success, track groundedness, failure modes, latency, and cost. Use human evaluation when outputs are subjective. 4. Build Production-Ready Projects Forget building 15 tiny tutorial apps. Build 2–3 serious projects that show: A live product GitHub repository System architecture Evaluation results Failure cases Engineering trade-offs Certifications can help, but make sure you’re actually building something alongside them. The roadmap is simple: Software Engineering → AI Systems → AI Evals → P...