Head of AI in Germany

AI Agent SaaS

Founded and built an AI agent SaaS for automated customer support and lead qualification, including implementation with pilot customers.

• Service → product transformation: productization from the agency into an independent AI agent SaaS. The starting point was a specific customer problem; the product was developed together with the customer.
• Developed and launched AI agents for website inbound, lead qualification, and customer service, reaching €8K MRR.
• Structured and led a remote team across engineering, LLM ops, and customer enablement.
• Case PTC Auto (e-commerce on Shopify): connected an AI support agent to the store, automated product data & support workflows, reducing workload by ~10–15 hours per week per support employee.
• Set up GDPR-compliant data processing for the AI agents: data processing agreements, deletion policies, and customer data storage locations.
• Assessed agents against the EU AI Act (risk class, transparency requirements) and built them accordingly.
• Addressed customers’ compliance and security requirements (questionnaires, evidence, contracts) to make sales possible in the first place.
• Built technical safeguards into the product to prevent agent misbehavior: hallucinations, escalation to humans, and logging.

• Governed multi-agent orchestration for regulated, EU-based companies – self-hostable, compliant with the EU AI Act and GDPR („by design“), BYOM (own models/GPU).
• Two-gate governance: agent deliberation + mandatory human approval, complete signed audit trail; graduated autonomy model („internal → autonomous per skill“).
• Verified knowledge graph („Company Brain“) with source evidence for each answer; proprietary orchestration framework (Virtual Team Framework).
• Industry solutions for financial services: compliance monitoring, invoice and contract review; hands-on development with LLMs (including Anthropic/Claude), agentic workflows, RAG.
• Development of the governance-focused multi-agent platform TeamIntel (see AI reference projects).

Conducted an independent technical assessment of an AI-enabled software platform, combining AI risk auditing, cybersecurity analysis and software architecture review. Reviewed application components, APIs, data flows, LLM integrations, retrieval-augmented generation, multi-agent orchestration, authentication, tenant isolation, dependency vulnerabilities, AI governance and model lifecycle controls. Authored a technical audit report with a structured risk register, source-code evidence, regulatory references, corrective actions, AI system inventory, risk classification, remediation roadmap and Key Risk Indicators.

Technologies: TypeScript, JavaScript, React, Next.js, Node.js, REST APIs, MongoDB, Redis, AWS serverless services, OAuth 2.0 / OpenID Connect, LLM APIs, RAG, vector search, multi-agent orchestration, Model Context Protocol, C4 architecture modelling, threat modelling, NIST AI RMF, ISO/IEC 42001, ISO/IEC 23894, OWASP guidance, MITRE ATLAS

• Leading AI development for aquaculture startup, optimising shellfish visual assessments with machine learning and computer vision.
• Development and systematic evaluation of ML/CV algorithms for shellfish condition and morphometrics, using Python, Pytorch and MLFlow.
• Analysis of model performance, including identification of failure modes and edge cases in production deployments.
• Design of annotation strategies and refinement of labelled datasets for computer vision tasks.
• Detailed analysis of system performance and communication of findings through publication-quality technical reports to investors and fellow R&D staff.
• Responsible for delivery of technical roadmap.

DOKKI

AI-powered digital health product development

• Shaped the product vision, requirements, priorities, and technical target architecture of an AI-powered solution for processing medical documents.
• Designed LLM evaluation, data processing, data protection/governance aspects, and subsequent product development; technical prototyping with Codex.

• Serve as AI lead for life-science solutions, integrating advanced AI models directly into company workflows and ensuring seamless deployment.
• Design and implement deep learning architectures (PyTorch, Keras) for complex biomedical challenges, including cell segmentation, multimodal omics analysis, and prediction of point clouds.
• Develop and deploy robust LLM-based systems, including RAG architectures and agentic workflows using LangGraph, to facilitate natural-language interaction with complex medical data.
• Lead cross-functional initiatives to apply foundation models and explainable AI (xAI) to clinical and evolutionary algorithms.

• Spearheaded AI-driven projects to enhance cognitive development, showing a strong commitment to innovative solutions in the AI space.
• Led AI strategy and implementation across multiple projects, ensuring alignment with business goals and driving major progress in AI applications.
• Oversaw the development and rollout of cutting-edge AI technologies, fostering a culture of continuous improvement and innovation within the team.

• Leading 20+ staff in development, site reliability engineering, and architecture.
• Leading the group-wide agentic AI initiative (Norway, Poland, Germany).
• Hands-on solution architect and AI consultant for over 50% of my working time on client projects in the publishing sector – from local publishers to international corporations.
• Strategic consulting and technical implementation of AI workflow platforms (n8n, Workato).
• Developing prototypes for traditional, AI-based, and agentic AI workflows.

• C-Level AI strategy consulting for companies in software development, transport and logistics, industry, medical technology, automotive, e-commerce, and event marketing.
• Leading the launch of new AI products and services.
• Analyzing use cases in R&D, sales, marketing, and service.
• Introducing AI solutions into everyday work.
• Technologies: Microsoft Copilot, Microsoft Azure OpenAI, AWS S3, Jira, Confluence.

Geeks Ltd is a UK-based technology company; WordUp is its AI-driven language-learning product focused on personalized vocabulary learning and intelligent educational experiences.

• Coordinate AI product delivery across Product, Engineering, Data, Operations, and leadership, translating user needs into scoped initiatives, sequencing work, surfacing blockers, facilitating hand-offs, and communicating progress.
• Own search, recommendation, retrieval, and content-enrichment features end to end, from requirements and architecture through Python/FastAPI implementation, testing, deployment, monitoring, and rapid iteration.
• Developed low-latency retrieval, ranking, and personalization services using AWS, OpenSearch, DynamoDB, embeddings, and reusable APIs, achieving <1s latency, 22% higher engagement, and 12% higher premium conversion.
• Use AI coding assistants for codebase analysis, scaffolding, refactoring, tests, debugging, and documentation while reviewing every output for correctness, architectural fit, security, maintainability, and user value.
• Represent technical work in planning and stakeholder discussions, gather requirements first-hand, challenge priorities constructively, explain delivery trade-offs, and help teammates make outcome-focused decisions.

• Analyzed patient data for various clients
• Developed complex analysis pipelines
• Performed quality assurance on methods

• Technologies: GoLang, JavaScript, TypeScript, AWS, Terraform, Git
• Conception of AWS infrastructure and existing services
• Analysis of IAM accounts and roles
• Setup of Cost Explorer and CloudWatch monitoring
• Setup of DynamoDB and S3 persistence of collected information
• Reporting and cost calculation
• Conception of Terraform deployment

AI Consulting | AI Training | Public Sector

Building a specialized AI consulting firm focused on the public sector and the organizational integration of generative AI.

• Development of AI-supported assistant and agent solutions for public sector organizations
• AI consulting, with a focus on public companies
• AI seminars and webinars for the public sector