France
Most enterprise AI projects never make it beyond proof of concept. My job is to make sure they ship and run at scale, in a large bank. 🎯 20 years in AI, 15 years of hands-on Python experience, and 100+ AI initiatives in production. Today, I’m Chief AI Architect & AI Design Authority for BNP Paribas Commercial Banking in France, owning the technical direction of the entire AI use case portfolio. What I do 👇 🏗️ Take AI from idea to production: target architectures, model and pipeline validation, governance, and go/no-go decisions for deployment 🤖 Drive the shift to AI-native, agentic systems: agentic architectures built around the Model Context Protocol (MCP), tools, and skills ⚙️ Transform engineering practices around copilots, AI agents, and AI-driven delivery 🔒 Set security and guardrail standards for a regulated banking environment 👥 Lead alongside 100+ experts across Data Science, Data Engineering, ML Engineering, and AI delivery, industrializing ML, Deep Learning, GenAI, and LLMs into robust, scalable, auditable, enterprise-grade systems 🚀 Ex-Founder & CTO in AI & Blockchain: owned the full arc from blank repo to systems running at scale ✍️ I write to 7,900+ followers on what production AI really looks like: agentic patterns, cost structures, and the gap between what ships and what’s hyped.
With 20 years of experience in Artificial Intelligence and 15 years of hands-on Python practice, I am Chief AI Architect and AI Design Authority of BNP Paribas Commercial Banking in France. I serve as the technical design authority across the AI use case portfolio, defining, steering, and validating the end-to-end AI pipeline, from target architecture and model validation to industrialization, deployment, and production. My role is to ensure that AI initiatives are built not as isolated experiments, but as robust, scalable, auditable, and enterprise-grade capabilities. I provide clear technical direction, structure solution choices, define governance principles, and issue Go / No Go decisions for production deployment. I help AI teams converge toward production-ready solutions through architectural leadership, governance, and decisive technical guidance. When a solution is not mature enough or not aligned with enterprise requirements, I define mitigation strategies, shape the target architecture, and steer them toward a viable path to industrialization. My scope includes model validation, end-to-end pipeline industrialization, and architecture consistency, ensuring that AI systems are sound not only in design, but also in execution, operability, and scale. I lead AI architecture and technical governance across the full lifecycle, from framing and design to industrialization, deployment, production, and long-term evolution. Working with more than 100 experts across Data Science, Data Engineering, ML Engineering, and AI delivery, we industrialize AI solutions spanning Machine Learning, Deep Learning, and Generative AI. Having contributed to more than 100 AI initiatives deployed in production, and drawing on previous experience as a founder and hands-on CTO in AI and Blockchain, I bring a combination of strategic vision, technical authority, governance discipline, and execution focus.
Lead Data Architect on innovative projects dealing with Artificial Intelligence, Blockchain and Big data, for BCEF IT (i.e IT BNP PARIBAS for french corporate and retail banking)
I was co-founder and hands-on CTO of the Web3 & AI start-up "Trust Flagger." Trust Flagger was the first Web3 UX reader and anti-fraud digital art solution for creators, collectors, and platforms. It was a truly disruptive image-based blockchain NFT search engine. We developed a major technological breakthrough to rebuild trust in the digital art of Web3. Our solution could simultaneously compare up to billions of NFTs to detect fakes, plagiarism, and inspirations instantly. It could identify an NFT from its artistic representation, detect or prevent fraud, and enable many other direct use cases. However, despite the technological advancements we achieved, we faced significant challenges in finding a sustainable market. The NFT landscape was evolving rapidly, with market volatility and skepticism toward Web3 technology impacting demand. This complicated environment made it difficult for us to scale our solution and achieve the adoption we had anticipated. Ultimately, we made the difficult decision to close our start-up, as the market conditions did not allow us to grow in a healthy and organic way and reach our full potential.
Independant Artificial Intelligence Solution Developer specialized in predictive solutions, leveraging Data Sciences to drive foresight, innovation, and business transformation. Alongside my professional journey, I've dedicated myself to designing and implementing impactful predictive AI models in Python, unlocking substantial value and enhancing operational efficiency by forecasting future trends.