Developer / Engineer → AI Engineer

AI engineering is built on Python. If you already code in another language, Python is fast to pick up. Focus on NumPy, Pandas, and data manipulation — these underpin every AI/ML library you'll use next.

Understand how models are trained, evaluated, and deployed. You don't need a PhD — you need to understand core concepts like supervised/unsupervised learning, overfitting, and model evaluation well enough to work with pre-built models and APIs.

The fastest path into AI engineering today is building with LLM APIs — OpenAI, Anthropic, Google. Learn to write structured prompts, chain calls, handle responses, and build simple AI-powered features into applications.

Nothing signals readiness like a shipped project. Build something real — a chatbot, a document summariser, an AI tool that solves a problem you care about. Put it on GitHub. This is your portfolio and it matters more than any certificate.

Update your GitHub profile, add AI skills to LinkedIn, and target companies actively building AI products. Junior AI Engineer roles are widely available for developers who can show LLM API experience and at least one shipped project.