The long version

I build AI systems, and I can tell you whether anyone actually needs one. Those turn out to be different skills.

I started on a sales floor at Tingis, selling energy and insurance contracts into the French market in French, to people who had not asked to hear from me. Inside six months I went from a new agent to one of the strongest performers on the floor. What that work teaches you is not persuasion. It is that people rarely state the thing they actually want, and that your job is to find it before you propose anything.

At devUP I moved into delivery, managing software projects across two teams websites, platforms, mobile applications and SaaS products, serving industries with very little in common. The same lesson arrived at a larger scale: the projects that fail usually fail because nobody translated the brief, not because the engineering was beyond anyone.

Since starting my master's I have been building the systems myself. AI agents, both hand-written and orchestrated through n8n. Machine learning models. Fine-tuning and retrieval-augmented generation. I took the work on in my first year rather than waiting for the degree to finish, because the interesting part is the gap between a vague ambition and something specific enough to evaluate.

I am looking for a role as a project manager, AI engineer or data scientist. The problems I want are the complex, quantitative ones — the sort that are not yet well defined and will not survive a guess.