Q: Do I need a degree or master's to become an AI Engineer?

No. And going back to school is usually the slowest, most expensive way to make this transition.

Here's the reality of how hiring works in this field. A degree is a proxy: it signals you probably know things. But hiring managers always prefer a better proxy when one exists, and in AI engineering a better proxy is available: deployed systems they can click. A working RAG application with a live URL and a commit history proves more than a certificate from any university, including the famous ones.

There's also a timing problem. The field reinvents itself every few months. University curricula move slower than that, so by graduation, much of what was taught is dated. Meanwhile, someone who spent those same months building and deploying real systems has current skills and public proof.

Where degrees do still matter: some large enterprises use them as HR filters, and if you already have one (in anything), it can help with those filters. But nobody should fund a master's to become an AI Engineer. Fund a portfolio instead.