01.04.2026 aktualisiert
100 % verfügbar
AI Governance and Data Privacy Specialist with Legal Background
Berlin, Deutschland
Berlin +100 km
Bachelor in LawSkills
ComplianceCompliance-SchulungenGovernance-Risikomanagement und Compliance
I am one of a very small number of people in the world who simultaneously holds 18 years of active legal practice, a Software Engineering degree, and IAPP certification as an AI Governance Professional — and has used all three in the same role.
That combination is not accidental. I spent 15 years as a practising Lawyer at the Tribunal de Justiça de São Paulo, the largest court on earth by caseload, with 20 million active cases and 2,400 judges. I then retrained as a Software Engineer in Berlin.
Today I lead AI governance at Krisenchat, Germany's largest digital mental health platform for minors, where I am the sole architect of EU AI Act compliance for AI systems classified as high-risk under Annex III, with documentation approved by the Berliner Beauftragte für Datenschutz und Informationsfreiheit and the Bundesministerium für Familie.
Along the way I contributed a full ML pipeline — data processing, feature selection, neural network design, XAI interpretation, MLOps, and logging, to research published in Scientific Reports (Nature portfolio), working directly with Dr. Vikram Sunkara, Head of Explainable AI for Biology at Zuse Institute Berlin. What this means in practice: I understand what engineers are building. I understand what regulator will demand. And I have spent 18 years writing documents that hold up in court.
If your organisation is navigating the EU AI Act, building high-risk AI systems, or needs governance that actually gets implemented rather than filed away, I am the person you are looking for.
Top skills
AI Act • AI Governance & Ethical Implementation • General Data Protection Regulation (GDPR) • ISO/IEC 42001 • Risk Assessment
Erfahrung
Berufserfahrungmehr als 10 Jahre
Freelancer seit2023
Sprachen
DeutschgutEnglischverhandlungssicherPortugiesischMuttersprache
Projekthistorie
I am the sole architect of EU AI Act compliance at Germany's largest digital mental health platform for minors; an organisation whose AI systems are classified as high-risk under EU AI Act Annex III, handling sensitive mental health data of children and young adults at national scale. 120+ staff · 450+ counsellors · 150,000+ crisis interventions.
What I built here:
EU AI Act: Own end-to-end operationalisation, translating legal obligations into enforceable technical, organisational, and product-level controls aligned with ISO/IEC 42001, ISO 27001, and GPAI governance standards. High-Risk AI Lifecycle: Design and govern AI system lifecycles across data sourcing, model development, deployment, monitoring, and decommissioning, embedding risk management, human oversight, traceability, and post-market monitoring directly into MLOps and product workflows. Federal Regulatory Approval: Authored compliance documentation approved by the Berliner Beauftragte für Datenschutz und Informationsfreiheit and the Bundesministerium für Familie. Auditability: Architect AI data flow and accountability models enabling real-time auditability, conformity assessment readiness, and incident response across engineering, legal, security, and product. Leadership: Govern across engineering, clinical, legal, and C-suite stakeholders, lowering regulatory exposure while preserving delivery speed.
The Zuse Institute Berlin is a state research institute of the Land Berlin, connected to 150+ scientific institutions.
I was embedded directly in Dr. Vikram Sunkara's Explainable AI for Biology group, one of Europe's leading XAI research teams. Two things happened here that don't often happen in the same role.
First: I developed the institute's first-ever Data and AI Governance Framework, compliant with GDPR and the EU AI Act, establishing privacy-by-design as the institutional standard for all advanced AI research at ZIB.
Second: I contributed a full ML pipeline to the research project that produced a publication in Scientific Reports (Nature portfolio).
My contribution covered the entire technical stack: data processing and cleaning, feature selection and engineering, neural network architecture, explainable AI interpretation, MLOps pipeline, and logging infrastructure.
The project was led by Dr. Vikram Sunkara, Head of Explainable AI for Biology at ZIB and the German Rheumatism Research Centre Berlin. This is what separates AI governance work that holds up from AI governance work that gets filed away: understanding what is actually being built, at every layer of the stack.
Conducted complex gene dataset analysis, integrated scientific research into software solutions, and implemented IT and data security protocols. Created training programs to develop privacy mindset within the company.