Three years ago I was designing transportation infrastructure with a Civil Engineering degree. Today I build production AI systems, multi-agent pipelines, RAG architectures, and LLM inference systems at scale. The switch wasn't luck. I did a structured Data Science program, built projects obsessively, and learned by shipping, not just studying. Now I work as an AI/ML Engineer at NexusLink, where I've cut inference costs 60%, reduced processing time 40%, and improved model accuracy 30%. I've also built and deployed 4 production-grade AI systems on my own from investment-memo agents to satellite risk analysis proof that a non-CS background isn't a wall, it's just a different starting point. If you're in a "non-tech" field wondering if an AI/ML career switch is realistic, or already switching and stuck on what to actually build/learn book a call. I'll map out the exact steps I used, not generic advice.