Prompt Engineering Expert

CXO AI OS is an agent system made up of six components. Instead of using AI as a chat window, it creates a system that understands a company’s context, makes decisions according to its rules, and acts on its behalf.

• For mid-sized companies: a guided sprint followed by ongoing operations for a team, department or prioritized cluster, based on an AI assessment
• For self-employed professionals: a program where participants build their own agent system
• Sequence in the company: assessment, prioritization, sprint, operations
• Implementation in Claude Cowork or ChatGPT Work, without coding
• Architecture: Chief of Staff, Goals, Advisors, Agents, Context, Catalog

AI Readiness - Part 3: Creating an e-book on the use of AI in software testing

• Designed and created an e-book on the sensible and safe use of AI in software testing from the perspective of an experienced test expert.
• Used generative AI (ChatGPT, Perplexity Pro) as a sparring partner for structuring, wording suggestions and creating variations, with all content finally reviewed and approved using my own expertise.
• Developed practical insights into the opportunities and risks of AI in testing, with a special focus on collaboration between testers and AI instead of “tester vs. AI”.
• Title: “11 starke Gründe: Dream-Team statt Rivalen - Tester und KI sind gemeinsam unschlagbar”
• Subtitle: “Wie Mensch und Maschine im Softwaretest das perfekte Team bilden – und warum reines KI-Testing riskant ist.”
• Planned use of the e-book as a basis for workshops, customer meetings or internal training.
• Technology: Generative AI, ChatGPT, Perplexity Pro, Microsoft Word, Adobe Acrobat, many years of hands-on professional testing experience, common sense.

• Instructor for an AZAV-certified AI training program for working professionals; designed in February 2026, with five cohorts each running for one month from March 2026
• Designed and created all modules and learning materials
• Topics: AI fundamentals, prompting, use cases in communication, analysis, and processes, agents and workflows, the EU AI Act, and GDPR
• Taught small groups of 3 to 9 participants from different professional fields and levels of seniority
• Provided individual learning support throughout each course
• Result: completed five cohorts with around 500 hours of live instruction

• Designed and developed a production-ready data platform based on Microsoft Fabric for an e-commerce company
• Built a scalable Medallion Architecture (Bronze, Silver, Gold) with Lakehouse and Delta Lake as the foundation for analytics and AI applications
• Developed a metadata-driven ETL platform with PySpark and a generic Incremental Loading Framework (SQL Server → Bronze → Silver → Gold)
• Developed reusable components for Microsoft Fabric Notebooks to standardize data integration, transformation, and validation
• Implemented automated data pipelines including monitoring, logging, error handling, and Delta MERGE strategies for stable production operations
• Built a business layer architecture for reporting, data warehousing, and reusable data products
• Integrated heterogeneous data sources via SQL Server, REST APIs, Amazon SP API, and Google Analytics 4
• Worked closely with business departments to analyze business requirements and translate them into scalable data architectures

Technologies: Microsoft Fabric, PySpark, Python, SQL Server, Delta Lake, Lakehouse, OneLake, Data Factory, Data Warehouse, REST APIs, Amazon SP-API, Google Analytics 4

• Advise early-stage startups on product vision, roadmapping, and GTM strategy, combining PMP and Stanford PM training with hands-on technical execution.
• Lovable: built and led a 200+ member community program for AI-native founders, bridging real-time founder feedback into product roadmap decisions.
• Lead customer discovery and OKR design engagements, scoping AI integration opportunities across client products.

• Documented complex financial reporting processes in deep-dive sessions with subject matter experts
• Analyzed and mapped the 3-tier data flow SAP – Essbase – HQ (984 account entries, triple chart of accounts)
• Identified the biggest time drains (40 % of close time)
• Evaluated technologies (AWS, Microsoft Fabric, Custom/Hybrid) with cost-benefit analysis
• Created a validation rule catalog with 351 rules as the basis for pre-submission automation
• Business case: estimated savings potential of 480–960 T€/year for the EAR region
• Hands-on implementation with Microsoft Fabric, RAG, AI agents/Tool Calling and n8n; productive use of Microsoft Copilot and Copilot Studio
• AI-supported project management workflows (minutes, tasks, knowledge synchronization)
• Stakeholder management at senior management level (EAR Accounting, IEA IT, TFSC Japan), workshops and training on AI tools

Technologies: Microsoft Fabric, Copilot Studio, Claude AI, Python, Power BI, SAP, Essbase/SmartView, Excel (VBA), Notion, SharePoint

• Development of a system for capturing, storing, and using knowledge
• Assessment of the current status and requirements for capturing employees’ tacit knowledge
• Creation of the appropriate taxonomy for the individual specialist areas
• Establishment of a suitable technical architecture
• Conducting expert interviews with the help of Artificial Intelligence (AI)
• Concept for data backup
• Analysis and evaluation of the approach and results
• Incorporation of organizational changes

The client operates a SaaS platform for managing rail and intermodal transport (Rail-Flow Transport Management Platform).

For two of its customers, it was looking for a 3-month project management replacement. Both customers offer rail and intermodal transport services. Implementation progress differs: one customer is already live and wanted its Phase 2 enhancements implemented; the other customer is implementing its MVP and entering an intensive testing phase.

As part of the assignment, project management was taken over, including management of the internal development team (offshore Turkey).

• Took over complete project management for 2 customer projects, including the roles of Product Owner and Co-Scrum Master
• Managed agile implementation teams consisting of business analysts, implementation consultants, developers (offshore) and QA staff
• Ensured compliance with and further development of project governance
• Planning and rollout management: creation and maintenance of project and rollout plans as well as coordination of role assignments with the client’s management
• Requirements and change management: management of contractual requirements, bugs and changes
• Customer and project communication: organization and moderation of status meetings and steering committees
• Identification of project risks, initiation of countermeasures and escalation
• Ensured correct and timely invoicing for project services together with Finance

Methods: Scheduling (forward- and backward-based), including milestone planning, structured interviews, multi-project management (in English)

Tools / Technologies: Jira, Confluence / Atlas, Claude (Skills, Artifacts), MS Outlook

• Fundamentals of electronics measurement, electropneumatic circuits & protective measures according to DIN-VDE
• Installation, wiring and commissioning of PLC-controlled Systems

• Functional requirements management for DIVID, the Umweltbundesamt platform for administering the single-use plastics fund. Focus: entitled parties, sub-entitled parties, and benefit reports.
• Consolidation and analysis of specifications, Jira, Confluence, functional concepts, and UX designs. Independent structuring and delimitation of requirements, as well as identification of contradictions, gaps, and dependencies.
• Creation and quality assurance of implementable user stories with clear, testable acceptance criteria. Preparation of decision alternatives and coordination with business, development, UX, and QA through team refinement.
• Conducting manual and technically assisted accessibility tests. Coordinating findings with QA and the Product Owner for further planning and implementation.
• Result: more consistent requirements, clearly defined processes and stories, and transparent open decisions. Separation of assumptions from confirmed requirements; better basis for implementation, refinements, and QA test cases.

Tools used: Jira, Confluence

• I support medium-sized clients with their funding needs.
• I evaluate operational business processes and translate complex legal and regulatory requirements into business requirements, target models and actionable roadmap epics.
• I use Generative AI tools and automation in a targeted way to efficiently create requirements documentation, process analyses, evaluations, meeting preparation materials, customer analyses and decision papers.

• Develop custom AI agents delivering 90%+ reduction in manual workload and significant efficiency gains
• Provide end-to-end AI strategy consulting: from digital assessment to implementation and change management
• Design and deliver tailored training programs and workshops on AI adoption, prompt engineering, and automation
• Support clients in implementing scalable AI solutions integrated with existing technology stacks
• Focus areas: AI strategy, automation, workflow optimization, and capability building

• Claude Code subagents, MCP, Pydantic V2, pytest, bandit

• Designed and shipped 3 specialized agents that hand work down a line: a research agent writes a cited implementation spec, a coding agent builds the modular code and its tests, a review agent ranks findings by severity and applies the fixes. Each handoff is a structured document, so no stage depends on another agent's context window.

• Connected the research agent to an academic-research MCP server (Semantic Scholar, ArXiv, Hugging Face Hub, citation snowballing) so every reference traces to a tool result rather than the model. Gated commits behind ruff, mypy, pytest and bandit, required human sign-off before installs and commits, and persisted session state on disk so long runs survive a context reset.

• Owned the development of partner-critical onboarding processes of the B2B2C-facing SaaS platform.
• Collaborated cross-functionally with engineering, design, and enterprise clients to deliver a scalable and API-first onboarding flow.
• Delivered the company’s main initiative — dynamic product — in close collaboration with internal SMEs and energy supplier clients.
• Increased successful user activations by 10% through streamlined ADDRESS API integration and real-time monitoring tools.
• Defined and prioritized product roadmap based on business goals, client needs, and platform vision.
• Led discovery sessions and co-creation workshops with customers, turning insights into validated product opportunities.