Experience
- Lead end-to-end GenAI engagements: discovery, architecture, hands-on implementation, and go-live support.
- Championed company-wide agentic engineering adoption: led research and industry networking, hosted internal workshops on best practices, and built an internal scaffolding repository to standardize and accelerate team-wide adoption.
LaunchPad (Internal) — Built a modular RAG accelerator framework on Azure for enterprise chatbot deployments; extended it with an agentic architecture to automate multi-step workflows. Tech: Python, FastAPI, Azure OpenAI, LangChain, Vue 3.
Fiducia 4.0 (Puratos) — Developed ML system predicting QC scores across multi-plant food production. Integrated raw material, process, and QC data sources into automated Azure ML pipelines. Enabled proactive quality control for Belgian and Mexican facilities.
- Designed and implemented GenAI solutions (document intelligence, process optimization) using LlamaIndex and LLM APIs.
- Mentored engineers in applied GenAI patterns, delivery practices, and client communication.
BioSignature 2.0 (Johnson & Johnson) — Led consolidation of multiple microservices developed by different teams into an efficient, streamlined, modular data and ML pipeline utilizing event-driven architecture and AWS Step Function. Reduced prediction turnaround from days to hours. Tech: Python, AWS (Step Function, SageMaker), KServe, Argo, Kubernetes, Jenkins.
- Coached junior ML engineers and interns across the full lifecycle with emphasis on engineering quality.
Dynamic Pricing (Proximus) — Built reinforcement-learning-based dynamic pricing system that drove 100% profit growth within nine months. Tech: Python, PyTorch.
Chatbot (BNP Paribas Fortis) — Developed a secure on-premises chatbot service with Llama 2.
- Streamlined pipelines with Azure Data Factory/Synapse and Azure DevOps.
Demand Forecasting (Unilever) — Developed sale and demand forecasting applications to reduce shortages and overproduction, shaping production strategies across facilities. Tech: Databricks, PySpark, Azure (Synapse, Cognitive Services).
- Built NLP feature extraction pipelines with BigQuery to support strategic product decisions.
- Delivered NLP, web scraping, and optimization projects end-to-end.
- Developed ML models for semiconductor packaging optimization; reduced product development timelines by 20%.
- Led thermal/structural analysis workstreams influencing reliability and design decisions.