Description

I am an AI Engineer specializing in LLM-based systems, agentic AI architectures, and end-to-end MLOps pipelines. With experience at the European Parliament and Proximus, I design and deploy production-grade AI solutions — from secure on-premise LLM workflows to multi-agent systems for business automation.

My expertise spans the full AI engineering stack: LangGraph-based agentic workflows, RAG pipelines, LLM fine-tuning, containerized deployments (Docker, CI/CD), and cloud/on-prem infrastructure (Azure, GPU management). I hold an MSc in Data Science from École Polytechnique (Paris) and have published research at CVPR 2023.

I help companies build reliable, scalable AI systems — whether it's automating compliance processes, building intelligent agents, or establishing robust MLOps practices.

Languages

English
Native or bilingual
French
Native or bilingual
Dutch
Basic

Workplace preferences

Can work on-site

Bruxelles (up to 50km), Lille (up to 10km), Anvers (up to 10km)

ENGIE
AI Engineer & Python Software Engineer
ENERGY AND UTILITIES
March 2026 - Today (3 months)
Brussels, Belgium
Core contributor to the Risk Digital team, building and maintaining an internal Python library for energy trading risk calculations. Designing an AI Agent to automate risk report generation using the library, leveraging Azure OpenAI and agentic workflows.
• • Building agentic AI workflows for automated risk report generation using Azure OpenAI and LangChain
• • Core contributor to internal Python library for energy trading risk calculations
• • Designing and integrating APIs for data retrieval and report automation with FastAPI
• • Working with cloud data infrastructure (AWS Athena) and Azure OpenAI services
Tech: Python, Azure OpenAI, LangChain, FastAPI, AWS Athena
Python AWS Développement Back-End Architecture logicielle Algorithmes et structures de données
Parlement européen
AI Engineer
PUBLIC SECTOR
February 2025 - February 2026 (1 year)
Brussels, Belgium
Developed secure, on-premise LLM-based solutions for compliance automation in a highly regulated environment. Designed end-to-end agentic workflows ensuring data sovereignty and full security compliance.
• • Built E2E agentic AI workflows for compliance automation using LangGraph with local LLMs (VLLM)
• • Set up on-prem AI infrastructure: CI/CD pipelines, containerized environments (Docker), GPU management
• • Implemented secure API architecture (FastAPI) with logging, monitoring, and governance controls
• • Managed MLOps lifecycle with MLflow: model versioning, experiment tracking, and deployment
• • Fine-tuned LLMs and implemented guardrails for enterprise-grade security compliance
Tech: Python, LangGraph, VLLM, MLflow, PostgreSQL
LLM Fine-tuning LLMOps Python Agent IA MLflow
Proximus Ada
Data Scientist – GenAI & Agentic Systems
TECH
May 2024 - December 2025 (1 year and 7 months)
Brussels, Belgium
Specialized in building agentic AI systems and GenAI solutions to automate business processes. Designed multi agent architectures for document automation, B2B sales intelligence, and security testing.
• • Designed and deployed agentic AI systems with LangGraph: RAG chatbot, Postgres AI Agent for B2B sales, Pentest Agent, LLM-based process automation
• • Built document summarization pipelines for large-scale document processing
• • Implemented MLOps infrastructure: LLM tracing, model versioning (MLflow), CI/CD on Azure DevOps
• • Containerized deployments with Docker; orchestrated workflows with Apache Airflow
• • Mentored colleagues on agentic systems design and software engineering best practices
Tech: Python, LangGraph, CrewAI, Autogen, RAG, MLflow, PostgreSQL, Airflow, Azure DevOps, Docker
Python CI/CD Agent IA RAG LLMOps