Mohamed Saadi — Paris
Enterprise AI Platform Architect.
I design and build the infrastructure where AI systems go from research to production — reliably, at scale, and fast enough to matter.
10 years. Every paradigm shift: Big Data, Cloud Native, MLOps, Agentic AI. Each time, arriving before the market had a standard playbook. Research at LIP6/CNRS (multi-agent systems, 2016) is what the industry now calls the theoretical foundation of autonomous AI.
Built the production data platform before Big Data was standard at French utilities.
Built the MLOps stack from scratch when the term was still a conference topic.
LLM orchestration and agentic workflows grounded in 2016 CNRS research on autonomous agents.
Case Studies
All cases →Experience
All →-
EDF (via NeoStair EURL)
Senior Solution Architect — AI & GenAI Platform
Oct2021 - Current
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EDF (via NeoStair EURL)
Solution Architect — Cloud Native AI/ML Platform
Oct2019 - Sep2021
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EDF
Big Data Engineer — Data Platform & Decision Systems
Oct2017 - Sep2019
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Sanofi
Machine Learning Engineer — Supply Chain Forecasting
Feb2017 - Aug2017
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LIP6 — CNRS Research Laboratory
Research Engineer — Distributed Multi-Agent Systems
Nov2015 - Jul2016
Published Research — LIP6 / CNRS Paris, 2016
A Multi-Agent Negotiation Approach for Supply Chain Management
188 pages · Theoretical foundation of today's Agentic AI
Architecture Diagram
The Infrastructure Path to Enterprise AI
Cloud Native → Data Platform → MLOps → Agentic AI
Available for senior missions
AI Platform Architecture · MLOps · LLMOps · Agentic AI · GenAI Platform
Paris region & remote · via NeoStair EURL
- linkedin /
- github /
- malt /
- saadi@neostair.com