David vonThenen

David vonThenen is an AI/ML Engineer where he focuses on production AI systems, enterprise AI data retrieval strategy, and architectures for explainable, governable, and reliable AI. His work spans agentic solutions, various RAG architectures, AI memory systems, multi-agent solutions, OpenSearch, data lineage, provenance, and AI governance. David has more than 20 years of experience building production software across AI/ML, speech and NLP, Kubernetes, cloud-native platforms, storage, virtualization, and backup/recovery. He combines hands-on engineering with technical strategy, open-source leadership, developer advocacy, and customer integrations. He has spoken at NVIDIA GTC, Devoxx (France, Poland, Greece, UK, Morocco), Open Data Science Conference (ODSC), WeAreDevelopers, and SCaLE on topics including explainable AI, agentic systems, model quantization, multimodal ML, and small language model training. His mission is to help teams move beyond AI prototypes and build systems that are observable, reproducible, trustworthy, and ready for production.