Product Managers in Munich

• Clarification of project objectives, scope and the target business vision for building the AI-based knowledge database.
• Derivation of the initial architecture and implementation strategy for the Zasterbot chatbot, including separation of the MVP and further development stages.
• Development of a target business vision for building a structured knowledge database and integrating a future chatbot.
• Derivation and prioritization of use cases for information retrieval and provision by the chatbot.
• Modeling of data structures and flows for the effective organization of the knowledge database on the Base44 platform.
• Design and implementation of data models for storing and linking relevant information.
• Development of processes for extracting, analyzing and preparing raw data for the knowledge database.
• Ensuring data consistency and quality as the basis for the future chatbot.
• Planning the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) for precise and context-specific answers.
• Implementation of functions for analyzing and displaying data from the knowledge database.
• Use of the Base44 platform with JSON Schema-based entities and a flexible permission concept.
• Implementation of Deno functions for backend logic, event processing and connecting external APIs.
• Integration of OpenAI services for initial data analysis.

• 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.

• Established a new venture focusing on AI-powered UX and rapid prototyping

• Leading the development of an AI-based prototyping framework and prompt optimization for product design

• Managing stakeholder relationships and strategizing go-to-market approaches

• Planning and creating coaching programs (to be launched in 2025) on AI-driven product discovery

• Developed internal processes enabling prototype creation in minutes

• Published best practices and insights on LinkedIn, driving industry interest and awareness

• Responsible as a project manager for several launch projects, including setting up processes and procedures
• Driving existing business

AI Assistance and Target Vision for Partially Autonomous Energy Portfolio Management

Building an AI control layer directly on the up-to-date daily live portfolio of a large energy provider — not as an isolated pilot, but as an operational extension of the existing DB1 and portfolio management. The goal is the gradual development from assistance through monitoring/alerting to analysis agents with Human-in-the-Loop approvals, supplemented by a role-specific System of Engagement alongside the BI System of Record. At the same time, the business case, target vision and management pitch compared with static monthly reporting are being developed.

• AI control layer: Design and build on the existing live portfolio data product (several million contracts) — development stages assistance → monitoring/alerting → agents with Human-in-the-Loop approvals.
• LLM-supported data analysis: Semantic queries, SQL/tool integration and additional RAG components based on portfolio, plan-versus-actual and data quality data (Azure OpenAI, Snowflake), with drill-downs to individual contract level.
• Analysis agents: Multi-stage agents for variance and driver analyses of churn, price adjustments, volumes and procurement costs.
• Views concept: Role-specific interfaces for business units, management and C-level as a System of Engagement alongside the BI System of Record.
• Business case & pitch: Target vision and cost-benefit argumentation compared with static monthly reporting.
• LLM setup (privacy & security): Coordination with IT Security and Data Protection — EU region, data separation and approval processes.
• Agent architecture: Multi-stage agent pipelines (analysis → validation → summary) with documented data sources, tool calls, review steps and source references for each statement.
• Data foundation: Built on the up-to-date daily DB1 data product (Snowflake, dbt) — portfolio, plan-versus-actual and data quality metrics as the common basis for all AI analyses.
• Guardrails & evaluation: Evaluation and approval processes for LLM responses relating to management-relevant statements — test sets, metrics and human review.
• Prototyping & validation: Iterative validation of agent responses with the business unit — test question catalogue, feedback loops and response quality for each release.
• Roadmap & development stages: Detailed stages from assistance → monitoring/alerting → partially autonomous management, including transition criteria and governance for each stage.
• Integration: Integration into the existing BI and data landscape — BI remains the System of Record, while the AI layer provides interactive drill-down paths as the System of Engagement.
• Enablement: Enablement of business users — prompting guides, training and an operating model for ongoing use.
• Management: Coordination of business units, Data Engineering, IT Security and Data Protection.
• Change Management: Communication and expectation management with business units and management throughout the development stages.

Results:

• Built on an existing up-to-date daily data product with several million contracts
• Established an LLM setup coordinated with Data Protection and IT Security in the EU region, including data separation and approvals
• Defined three development stages through to partially autonomous management
• Designed role-specific views for business units, management and C-level
• Developed the business case and management pitch for the development stages
• Established an iterative response-quality validation process with the business unit
• Designed the operating model for assistance operations and initiated validation

Stack: Azure OpenAI, Azure AI Foundry, Snowflake, dbt, React, TypeScript, Entra ID, RAG, Agentic AI, analysis agents, Human-in-the-Loop, Prompt Engineering, LLM Evaluation, LLMOps, GDPR / EU region, Azure DevOps, Python, SQL, Change Management

• Certified Health Coach in Sleep, Stress Management & Recovery
• Mission is to transform lives, not bodies, achieving sustainable & life-changing results in all critical areas of life — from health and fitness to relationships, career, mindset, emotions, and resilience

• Driving app monetization and growth initiatives for Bundesliga products.
• Moderation of cross-team ideation workshops for idea generation.
• Amplitude Product Analytics, Google Ad Manager, Firebase.

An enterprise process mining and execution management platform that helps organizations analyze, visualize, and optimize their business processes using event data.

• Aligned 40+ engineering squads across 5 countries to deliver platform capabilities at scale, driving release infrastructure, change management, and rollout governance with zero post-launch defects for 1000+ enterprise customers
• Owned celonis studio platform roadmap prioritization, balancing technical investments, commercial priorities, and operational needs, driving 50%+ market share growth against legacy products
• Translated requirements into specifications, architectural decision records, and delivery plans in collaboration with engineering and UI/UX, resulting in a 20–30% increase in user engagement
• Drove the GA launch strategy, running pilot programs and customer discovery sessions to validate operational readiness and enterprise adoption

• Planning and implementation of compliance applications for customers
• Operational setup, expansion, support and risk assessment of the underlying IT platforms
• Responsible architect for the IT platforms and related interfaces
• Primary contact for technical topics, changes and releases, especially coordinating between manufacturers, the data center operator and the customers of sanctions monitoring
• Independent coordination of incident management / problem management
• Operational management of service providers and manufacturers, as well as performing non-organizational management tasks
• Technical contact in various internal and external IT customer projects (in some cases deputy project manager)
• Support in preparing offers for customer orders in application management for compliance applications
• Management of operational tasks and requests in sanctions monitoring

• Architected and built a GenAI-based automated asset-generation tool for social media campaigns using Nano Banana and Python. It takes a campaign brief, target audience, and two products as input, generates optimized prompts for image and text creation, and uses functions for text positioning, visually appealing overlays, resizing, and structured uploads to AWS S3.
• Engineered and built a multi-agent news intelligence platform with specialized roles including retriever agents (Tavily web scraping), synthesizer agents, and Claude as curator/orchestrator, designing autonomous agent collaboration patterns using LangChain and RAG.
• Built an autonomous customer service agent using n8n and LLMs, delivering end-to-end support automation with transparent reasoning, governance controls, and scalable workflow orchestration using Python and vector databases.
• Developed a financial validation engine featuring ML-powered anomaly detection for invoice plausibility, compliance automation, and risk mitigation using TensorFlow and SQL.
• Created a cost optimization application using OCR, AI, Pandas, and NumPy for data analysis to identify cost optimization potential.

• Built and scaled a data-science price engine across 8 EU markets, lifting fleet margin by ~2% on a €1.5B+ base
• Launched a generative-AI insights platform in 29 countries, cutting manual analysis by ~40% and driving weekly actions
• Led a hybrid team and aligned 100+ stakeholders to refine pricing logic and accelerate rollout across regions
• Set up KPI governance with WBR/MBR rhythms, reducing decision latency by ~30% across European pricing teams

• Discovery, scoping, strategy, assembling my team, implementation, regulatory approval and launch of a medical companion app within 5 months
• Led a team switching from project methodology to agile/lean methodology, set up team strategy and target KPIs, and developed features to customize physical products to individual use cases and needs
• Assessed and sharpened the concept of a patient portal for hospitals, set up resource and timeline plan, and recommended team setup, strategy and implementation
• Developed and implemented a 3rd party authentication feature in partner destinations, improved enrollment flow UX, and supported teams transitioning from project to product thinking
• Convinced major players in the transport and medical industry to enter long-term digital pilot partnerships to create value together

• Led the development of a circularity assessment tool aimed to help architects evaluate and enhance building circularity from an early design phase
• Conducted an in-depth analysis of the existing tool to map user flows and decode the underlying calculation logic
• Facilitated structured discussions with a cross-functional team and domain experts to refine the problem statement and define project priorities to deliver within a 6-week agile sprint
• Delivered a clickable prototype with a simplified user experience, integrating AI-guided assistance with smart tooltips, an ML-based material suggestion/matching logic and a custom GPT for value-added insights
• Tool is currently under consideration for continued development support by N3XTCODER and AI consulting support from Civic Coding Consulting

• Led development and management of advanced data products and reporting solutions, driving €11M revenue in 2023. Hired and mentored a product manager to enhance product capabilities, enabling brands to gain closed-loop measurement insights.
• Defined product vision and strategy for offsite product domain globally, enabling brands to engage their most valuable customers throughout the omnichannel customer journey.
• Initiated and led data-driven martech and adtech innovations, laying groundwork for AI-powered personalization and targeted marketing across 12 countries.