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CAREER PATH · 6 courses

AI Engineer

Move from developer to AI engineer: build features on LLM APIs, retrieval systems and agents, and run them in production safely and responsibly.

About 5 to 6 months, up to two courses at a time. 6 courses, 36 live one-on-one sessions, 54 hours with your trainers.

The job

An AI engineer builds software that uses AI models to do real work. They call language models from code, connect them to a company's own documents and tools, build agents that act on behalf of users, measure whether the answers are good enough, and keep the whole system reliable, affordable and secure in production. They are developers first: what changes is that part of the logic is now a model, which has to be tested, watched and governed like any other component.

Why now

The developer market is changing fast. Offers for generic developers are falling in France, while AI engineering is the role rising fastest, and AI is becoming part of everyday work. This path is built for developers who want to make that move with real engineering skills.

The journey

  1. STAGE 1 · FOUNDATIONS

    • Python for AI & LLM APIs

    • Agentic Coding with AI Assistants

    Both courses run at the same time.

  2. STAGE 2 · RETRIEVAL AND CONTEXT

    • RAG & Context Engineering

  3. STAGE 3 · AGENTS

    • AI Agents, Tools & MCP

  4. STAGE 4 · PRODUCTION AND RESPONSIBILITY

    • AI Evals, LLMOps & Deployment

    • Responsible AI & AI Security: EU AI Act & ISO 42001

    Both courses run at the same time.

Who it's for

  • Developers in any language (Java, C#, JavaScript, PHP and others) who want to move into AI engineering
  • Python developers who have not yet built features on LLM APIs, retrieval or agents
  • Data, automation and DevOps engineers with real programming experience who want to build AI systems properly
  • Developers who already experiment with AI and want a complete, production-grade method

Before you start

Real programming experience, in any language: you write, read and debug code as part of your work. Python is not required at the start; its basics are refreshed quickly in the first course. A use case from your own work to build on during the courses is strongly recommended.

What you'll be able to do

  • Build reliable features on LLM APIs in Python: structured output, tool calling, tests and cost control
  • Build retrieval systems that answer from your own documents, with citations and honest evaluation
  • Work with coding agents every day: give them well-scoped tasks, connect your tools through MCP and review what they ship
  • Design agents and workflows that do real work, with guardrails, human approval and evaluations
  • Take an LLM application to production: evaluations in CI, deployment, observability and a runbook
  • Build AI you can defend: EU AI Act, GDPR, AI security threats and governance

Certificates

A certificate of completion for each course, and a path certificate, “AI Engineer”, once all six courses are done.

Questions

How long does the path take?

About 5 to 6 months, taking two courses at a time where the path allows it. You can also go one course at a time, which takes longer.

I don't code in Python. Can I join?

Yes, if you already program in another language. The first course refreshes the Python basics quickly and goes straight to AI work.

I'm already a developer using AI. Do I start at the beginning?

The path is one package. If you already master a subject, tell us during the intro call and we will look at it together.

Can I take a break?

Yes, between two courses. Inside a course, the usual session rules apply.

In which language?

English or French, chosen at the start for the whole path: sessions, documents and certificates.

Will this get me a job?

Nobody can honestly promise that. The path builds the skills employers ask for today, and leaves you with a portfolio you can show.