AI Product Manager in Germany

• Support for a data, analytics and AI initiative in a regulated enterprise environment by structuring, evaluating and prioritizing several data-driven use cases based on business impact, feasibility, scalability, data maturity and governance requirements.
• Translation of complex business and analytics requirements into clear product, data and implementation logic, as well as preparation of decision-ready documents, target visions and roadmap inputs for stakeholder and management discussions.

• Hands-on development of AI-native product prototypes with specialized AI agents for research, requirements, business logic, UX/flow design, test case generation and quality assurance.
• Structured use and orchestration of AI agents through clearly defined roles, inputs/outputs and handover points; breaking down complex product tasks into verifiable work packages and iterative prototyping cycles.
• Establishment of human-in-the-loop quality gates to validate AI-generated results for functional correctness, consistency, completeness and feasibility; targeted rework cycles in case of deviations.
• Development of a regulatory GenAI/rules prototype for CRD VI with a structured decision flow, web UI, rule-based validation and automated test cases; iteration of the business logic through to a pilot-ready POC.
• Design of an AI-to-Action banking prototype: AI intent → consent → bank/product logic → conversion including admin console; translating the product idea into MVP scope, role model, user flows and clickable prototypes.

• Development of a digital audit application for inspections in medical facilities. The goal is to connect on-site data collection, voice recording, documentation and downstream processes in one end-to-end, AI-supported workflow.

• Design and development of a Flutter audit app with Claude Code for the structured execution and documentation of inspections.

• Processing of voice recordings captured in the app through automatic transcription and AI-supported creation of structured inspection reports, followed by an approval process

• Connecting various data sources such as email, Odoo 19, attendance records and Google Drive via n8n to automate billing and follow-up processes

• Automatic provision of required documents and email delivery through n8n-controlled workflows, including the use of LLMs for text creation

• Skills: Flutter, Claude Code, LLM Integration, n8n, Odoo 19, Google Drive, Process Automation

Evidence-led health intelligence platform turning published research into personal health protocols. It scores 430 habits, foods, and supplements against the studies behind them, and moves the score when the evidence moves. Built solo.

• Built the daily ingestion pipeline across PubMed, bioRxiv, and medRxiv: 43,000+ papers from 3,400+ journals processed into 230,000+ typed evidence claims, each one traceable back to the study it came from.
• Designed the six-factor evidence scoring model and the public changelog behind it, so no recommendation ever appears without the papers underneath it. 23,000+ grade changes recorded and explained to date.
• Shipped an entity information model connecting every intervention to its mechanisms, biomarkers, and outcomes: 118 biomarkers with region-specific reference ranges, 77 mechanisms, 32 graded outcomes.
• Built the personalisation layer: blood panel ingestion that reads lab PDFs with a vision model and corrects results for draw time against the user's wake anchor, plus Oura, WHOOP, and Withings integration for daily readiness context.
• Operate eleven specialised review agents over the corpus and codebase, covering paper curation, retrieval quality, health-claim compliance across EU and US regimes, and security.
• Shipped the Evidence Assistant, a RAG assistant that answers from the claim database and cites the underlying papers, plus a B2B practitioner tier, an Expo React Native app, and localisation across 3 languages and 7 markets.

Stack: Next.js 16, TypeScript, Supabase, pgvector, Anthropic Claude, Vercel, DeepInfra.

Digitalization of real-world locations using 3D/LiDAR scans to make spatial data usable for AI applications and derive concrete use cases and prototypes from it.

• Digital capture of real-world locations as a basis for faster planning and analysis
• Browser-based access to 3D data for easier use and coordination
• Conversion of spatial data into concrete use cases, prototypes and AI training scenarios
• Planning basis for urban development and other digital applications of the future

Keywords: LiDAR, 3D scan, AI, use cases, AI training, prototyping, Python, web development, data models, architecture

• Built and validated SupportPiloten, an AI-powered content operations service; won the first paying pilot customer
• Tested agentic workflows with Claude Code and Codex for analysis, research, documentation, and prototyping
• Continued developing my own AI product; training in AI governance, AI compliance, and the EU AI Act (ongoing)

• Orchestrate cross-functional delivery across organisational units in the Connectivity domain, aligning teams around integrated end-to-end, customer-testable value rather than isolated component delivery.
• Drive a shift from local component optimisation towards shared outcomes and a common delivery goal, increasing focus and enabling significantly faster integrated delivery.
• Coordinate across 15 cross-functional organisations in a highly complex OEM environment; bring Product, Engineering, Programme Management and specialist functions together to resolve dependencies and improve decision-making.
• Coach Product Managers, Product Owners and stakeholders on product responsibility, prioritisation, outcome orientation and aligned backlogs.
• Use Claude through an AWS Bedrock integration to analyse Jira and Confluence content, identify patterns, dependencies and quality gaps, and support structured product and delivery decisions.
• Establish AI-native requirements excellence with LLM-supported quality gates for epics, features, stories, acceptance criteria, roadmaps and task breakdowns; scale adoption through templates and prompt playbooks.

Driving AI model quality at scale — evaluating prompt-response accuracy, flagging edge cases, and maintaining SLA-compliant workflows across distributed global teams.

• Analyse AI prompts and side-by-side model outputs to assess response quality, factual accuracy, relevance, consistency, and compliance with project evaluation guidelines.
• Perform fact-checking, data validation, troubleshooting, issue identification, and edge-case review to improve quality standards across AI training support workflows.
• Use Google Sheets, Google Docs, and browser-based tools to document findings, maintain evaluation logs, track issue patterns, and support workflow optimisation in a remote environment.
• Create clear written justifications, review summaries, and KPI-oriented reporting focused on accuracy, turnaround time, documentation completeness, defect identification rate, and SLA adherence.

• Defined the vision, strategy, and roadmap of AI-powered analytics products, ensuring they met the business needs of Sales, Marketing, Finance, and executive teams across Europe.
• Collected business requirements, prioritized AI product features, and led Agile development of forecasting and analytics solutions. Defined product specifications, user stories, and acceptance criteria to ensure successful delivery.
• Collaborated with business stakeholders, Product Owners, data scientists, ML engineers and software engineers to transform AI models into scalable business products and integrate AI insights into operational workflows.
• Designed and implemented Generative AI solutions leveraging Large Language Models (LLMs) to automate reporting and enable natural-language querying of enterprise data, reducing manual effort by approximately 30%.
• Defined product goals and success metrics, tracked product performance and user adoption, and continuously improved the product based on user feedback and business results.
• Established data governance, master data quality and reporting standards across SQL, BigQuery and Power BI environments to ensure reliable, secure and scalable analytics.

• Independently managed the POS tender process for food service operations in department stores.

• Structured requirements gathering, both functional and technical.

• Created a management-ready specification as a basis for decision-making by management and IT.

• Market overview of relevant POS providers.

• Close coordination with Galeria's IT and business departments.

• Instructor for applied AI in the courses "AI Implementation Architect" and "AI Business Innovator"
• Running remote training sessions to qualify participants as "AI Implementation Architect" and "AI Business Innovator"
• Building n8n-based automations for the Digital Institut des Mittelstands

• Responsible for the concept, planning, and implementation of the product development of GetMyInvoices 2.0 and the subcomponent InvoiceRails
• Independent work on all aspects of the project, including concept, specification in tickets, and coordination of developers
• Creation, management, and prioritization of tickets to ensure all tasks are completed on time and with high quality
• Carrying out and/or coordinating tests and ensuring the proper implementation of the developed features and functionalities
• Close collaboration with developers to clarify technical requirements and ensure the implementations match the specifications
• Regular reporting on project progress and documentation of key decisions, changes, and risks
• Taking on the subject matter lead for all topics around e-invoicing and Peppol, especially in relation to the InvoiceRails component
• Internal consulting and knowledge sharing on e-invoicing and Peppol for other teams and departments
• Tracking market trends and new developments in e-invoicing and Peppol to continuously adapt the product strategy
• Ensuring the long-term scalability and flexibility of the products for future technical and regulatory changes in the e-invoicing area

Advising tech companies and founders on product strategy, customer discovery, AI-driven product development, and product operating models.

As a freelance employee / independent consultant, I supported a wide range of development projects and advised clients on digital innovation initiatives. A common role was acting as project manager / product owner at the interface between the client and the development team.

• Product Consulting — (Fractional) Product Owner, Freelance Product Management
• AI Services — AI consulting, training, vibe coding / agentic engineering, AI agents
• Tech Services — full-stack web development, design/UX, MVP delivery.