AI Systems Architect · Intelligent Automation
Regulatory Compliance · Legal Tech
Computer Science · Law · Economics
Diplom in Computer Science and B.Sc. Mathematics from Freie Universität Berlin, with foundational studies at KIT. Research spanning ML, game theory, and network security. Production systems in Python, Java, Scala, and Spark at terabyte scale.
Pursuing the Erste Juristische Prüfung (Staatsexamen) at FernUniversität Hagen. Specializing in digital law, GDPR, and the EU AI Act — embedded into architectures from the first commit, not added as an afterthought.
B.Sc. Economics at FernUniversität Hagen. Game theory, monetary policy, and quantitative methods — the analytical framework that translates technical decisions into measurable business outcomes.
"I move AI beyond the playground into secure, scalable, audit-proof production."
AI Systems Architect with over eight years building production-grade AI in regulated environments — with formal training in Computer Science, Economics, and Law. I design RAG architectures, LLM agents, and enterprise automation systems with GDPR and EU AI Act compliance embedded at the architecture level, not retrofitted at deployment.
At Universität Potsdam and Cisco, I built a Spark-based ML pipeline processing terabyte-scale network data, reducing analysis time from days to hours. At Audi AG, I delivered applied ML programmes in predictive maintenance from 2018 to 2025. At FAU Erlangen-Nürnberg, I teach Legal Informatics to LL.M. candidates at the intersection of AI systems and legal exposure.
I work across engineering, business, and legal requirements — and can evaluate a system against all three in the same conversation. That is not a soft skill claim. It is a structural capability with a concrete use case in every regulated AI deployment.