I ship AI to production.
RAG pipelines, autonomous agents, and forecasting platforms across 15,000+ locations in 40+ countries. I turn ambiguous problems into measurable systems, at Fortune 500 scale.
Retrieval, ranking, agents, evals, and the discipline of keeping them healthy after the demo is over.
I build production AI systems end to end. Most of my recent work is Fortune 500 deployments where the signal lives in messy enterprise data and the buyer is a non-technical executive who needs a number they can defend.
My path to AI started in aerospace engineering at TU Delft, with a thesis on neural networks for turbulent airflow simulation. That mathematical rigor became my edge. Today I work across RAG pipelines, agentic workflows, evaluation harnesses, and the production observability that turns a clever notebook into a system you can trust.
M.Sc. Thesis · TU Delft A Neural-Network-Coupled Variational Multiscale Method for 3D Turbulent Channel Flow Computational Fluid Dynamics · Deep Learning · Numerical Methods →Senior AI / GenAI Engineer
Jan 2025 - Present- Architected a demand-forecasting platform across 15,000+ locations in 40+ countries for a Fortune 500 QSR chain. Ensemble model improved accuracy 8 to 12% and automated 2,000+ campaigns monthly.
- Built the enterprise RAG pipeline and AI chatbot serving 20+ languages with sub-5-second responses: vector search, cross-encoder reranking, live grounding.
- Designed an autonomous BI operations agent for a Fortune 500 cruise-line operator: LLM monitoring across 30+ servers with human-in-the-loop governance. 60% faster incident resolution.
AI / Machine Learning Engineer
Apr 2023 - Jan 2025- Built an AI-powered Google Ads automation pipeline managing 20+ campaigns, cutting manual optimization 50 to 65%.
- Delivered 25 to 40% faster launches and 15 to 30% CTR lift via closed-loop optimization every 6 to 12 hours.
Computational Fluid Dynamics Engineer
May 2022 - Apr 2023- Simulated thermal and airflow models for data-center environments on HPC: cooling-risk analysis, rack-layout optimization, engineering recommendations for operations.
Software Engineer, Machine Learning
Oct 2019 - Sep 2020- Built a résumé-to-job matching system over 15,000+ résumés and 1,200+ job descriptions using OCR, embeddings and hybrid ranking. Cut screening effort 40 to 55%.
- Developed palm-vein biometric authentication with the Fujitsu SDK, reaching 99% correlation accuracy.
Enterprise RAG Pipeline & AI Chatbot
End-to-end retrieval for a Fortune 500 QSR chain: semantic search across thousands of locations, custom cross-encoder reranking, NeMo Guardrails. 20+ languages, sub-5s latency.
Demand Forecasting Platform
Ensemble forecasting (XGBoost + LSTM) across 15,000 to 20,000 locations globally. +8 to 12% accuracy, -6 to 8% stockouts, automated triggering of thousands of campaigns monthly.
Autonomous BI Operations Agent
LLM-based operations agent for a Fortune 500 cruise-line operator. Classifies 50 to 80 daily signals and recommends action with sandboxed execution and human-in-the-loop governance. -60% resolution time.