Fastest way to become an AI Engineer in 2026 | Skills, Projects & Salary
AI engineers are making $200,000+ a year and at companies like OpenAI, Meta, and Anthropic, some are earning more than $1 million+ a year.
But most people trying to break into AI engineering are learning the wrong skills, in the wrong order, and wasting months on things companies don’t even hire for.
This video cuts through the noise.
Based on real job postings, hiring data, and conversations with AI engineers at foundational model companies, I break down what AI engineers actually do and the fastest, practical roadmap to becoming an AI engineer in 2026 without a PhD or ML research background.
🚀 What you’ll learn
✅ AI Engineer vs ML Engineer vs LLM Engineer
✅ Skills companies actually hire for in 2026
✅ Whether you really need math or ML
✅ Python skills that matter (and what to ignore)
✅ Prompt engineering for real-world systems
✅ RAG, vector databases, LangChain & agents
✅ MCP, LLMOps & production AI basics
✅ Portfolio projects that actually get interviews
⏱️ Timestamps
0:00 AI Engineer salaries & reality
0:59 What AI engineers actually do
2:00 AI job market & salary data
2:46 Phase 1
3:45 Phase 2
4:55 Phase 3
7:00 Phase 4
9:02 Final advice
about me
I’m Maddy, a senior software engineer (prev. at Google), with prior internships at Microsoft, Morgan Stanley, IBM, and Amazon. Sharing my journey here – thanks for watching 🤍
🔗find me on other socials
Instagram https://www.instagram.com/madeline.m.zhang/
LinkedIn https://www.linkedin.com/in/madelinemzhang/
Tiktok https://www.tiktok.com/@madeline.m.zhang
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*disclaimer: views are all my own and do not represent any current / past employer(s)
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