The career roadmap
How to become an AI engineer, honestly
Most 'AI engineer' jobs are software engineering with new tools. Here's the roadmap we'd give a friend — the same one our academy walks people through.
The five stages
Foundations that don't expire
Mathematical analysis, algebra, computer fundamentals, one language known deeply. Skipping this stage is the single most common reason careers stall at year three.
Core engineering
Design patterns, software architectures, relational databases, automated testing, UML as a thinking tool. This is what separates engineers from code producers — and it's exactly what interviews probe.
Design patternsBuild and ship real systems
Full stack work, DevOps basics, security thinking. A system with real users teaches more than ten tutorials; owning it in production teaches more than a hundred.
Clean architectureThe agent era
Claude Code, Cursor, LLM APIs — used with briefs, verification and review. AI tools multiply stage 1–3 skills; without them, they multiply zero.
Claude Code guideReviewed practice
The rarest ingredient: someone senior reading your work weekly and telling you exactly why it isn't good enough yet. Find it in open source, in a great team — or in our academy, where it's the whole method.
The honest part
You don't become an AI engineer by collecting AI certificates. Employers — we're one — hire people who can take a problem they've never seen and dismantle it: with math, with architecture, with tests, and yes, with agents. The roadmap above is slower than a certificate. It's also the only one that compounds.
- A CS-related degree helps and covers stage 1 well — but proven ability beats paper. Our own academy accepts either a bachelor's in a CS field or demonstrable experience with strong fundamentals.
- From zero: years, honestly — stage 1 and 2 alone deserve 12–24 months of real practice. From working-developer level: stages 4–5 can land in months, which is exactly the academy's 2–3 month scope.
- For ML research roles, yes. For the vast majority of AI-engineer roles — building products on top of models — engineering fundamentals plus API-level model literacy matter far more than deriving backpropagation.
- Few move hiring decisions. Reviewed, verifiable work does. If you want a credential, pick one backed by months of reviewed work — that's what our badge registry is.