Quality Inspection Experts in Germany

Stabilization of a critical logistics outsourcing setup in the context of an SAP S/4HANA transformation. The focus was on restoring a reliable operational fact base between the client, logistics service provider, international supplier plants and the SAP/IT organization.

• Coordination between the client, global logistics service provider, international supplier plants, SAP/IT teams, Quality Management and the operational shop floor.
• Management, monitoring and operational correction of Inbound Deliveries; integration of Outbound Delivery processes.
• Analysis of interface, posting, batch and master data errors between SAP S/4HANA, logistics service provider, supplier plants and internal business functions.
• Significant reduction of critical inventory differences between the client and logistics service provider.
• Improved operational management capability in the logistics environment and creation of a common fact base.
• Reduction of recurring error patterns in the areas of Inbound Deliveries, inventory, interfaces, batch/posting logic and service provider processes.

Programming custom indicators with ProBuilder (for the ProRealTime platform)

6 months at RCP - Rabe Academy (basics - trading account - TWS Interactive Brokers) Focus: ETH price history - NVIDIA stock (NASDAQ and CBOE)

• 500 hours total (TradingView & ProRealTime), including approx. 1,500 hours of tick data analysis using ProRealTime

Systematic market analysis, development of custom indicators, pattern recognition.

• 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.

• Industry: Insurance, Trade, IT
• Customers & Projects: Consulting and selling insurance and similar services
• Main tasks: Insurance consulting (health insurance, retirement planning, wealth building); commercial services, inside and field sales; sales data analysis and forecasting; customer consulting and support; opening a new sales headquarters for private and business customers; business development & innovation management; business use case development; process optimization; stakeholder management; team leadership and training; preparation and delivery of trainings;
• Technologies used: Microsoft Office 365, Microsoft Teams, Jira, Draw.IO, Camunda 8, Java (8, 17,21,25), Git, Spring Boot, Spring Batch, Spring Data REST, Spring Web, Spring Security, J-Unit, Playwright, Lombock, Vaadin, H2, PostgreSQL (16, 17 18), pgAdmin, Docker, LLMs, JasperSoft Studio, JasperReports

Project: Defect Generation on Test-Bench Images of Metal Surfaces Environment: Automated Visual Inspection (AVI), Metallurgy & Manufacturing

• Objective & Implementation: Designed, architected, and trained Generative Adversarial Networks (Pix2PixHD / SPADE) for image-to-image transformation. Targeted generation of synthetic material defects (e.g., cracks, inclusions, scale) on rough metal surfaces under real test-bench lighting conditions for privacy-compliant and efficient dataset expansion (data augmentation).
• Technical Design: Implemented robust Generative AI and computer vision pipelines in Python and PyTorch. Used semantic segmentation approaches for mask-controlled defect synthesis and subsequent evaluation with EfficientDet object detection models.
• Business Impact: Massive dataset upscaling (10x) without time-consuming and costly physical test-bench runs, while significantly improving the detection performance of automated inspection systems.

Technologies & Skills Used: Python | PyTorch | SPADE | Pix2PixHD | EfficientDet | Machine Learning | Semantic Segmentation | Computer Vision

ETL 180 - Construction of 90 Km gas pipeline between Hamburg and Bremen. Supervision of welding, pipe lowering, coating, bending work and pressure testing. Quality assurance. Steel pipe with a diameter of 1,4 m and a wall thickness of 21mm.

Parameterization and support during the commissioning of water treatment

Project: New construction of municipal water treatment plant Dörenthe

• Checking the sensors for suitability, installation errors and parameterization.
• Coordination with the PL system for automation.
• Correction of errors

Tools: Endress & Hauser Tools

• Role: Simulation Engineer
• Environment: Mechanical Engineering / Visual Inspection
• Goals & Implementation: Simulation of photometric-stereo setups to determine the best positions for cameras and light sources for each specific part.
• Business Value: Enabled a low-cost and scalable solution for determining part-specific hardware setups.
• Tech Stack: Python, Blender

• Designed and developed a multi-tenant SaaS platform enabling organizations to build their own knowledge bases and chat with brand-customized AI assistants (white-label approach with dynamic branding per organization).
• Implemented a scalable RAG architecture with a GPT-4o tool-use loop, hybrid semantic search, and strict tenant isolation at database and search index level.
• Built persistent, project-like chat sessions including a streaming API (SSE), multilingual support, and speech input/output (STT/TTS).
• Delivered the cloud infrastructure as Infrastructure-as-Code, fully automated per-customer CI/CD pipelines, and an onboarding process for new tenants.

Technologies used: Python, FastAPI, Pydantic (v2 noted), Next.js, React, TypeScript, Tailwind CSS, OpenAI / LLMs (GPT-4o), Azure AI Search, Cosmos DB, Azure Blob Storage, Azure Cognitive Services Speech, Azure App Service, Azure Container Registry, Retrieval-Augmented Generation (RAG), Server-Sent Events (SSE), Docker, Terraform, GitHub Actions, REST, OpenID Connect (OIDC), Multi-Tenancy

• Lead Product Owner role for the BFSG pilot journey “Search and Book” across web and app, focusing on digital accessibility, UX, conversion, and regulatory implementation.
• Created and prioritized the product backlog; derived user stories and acceptance criteria from legal standards (BFSG, WCAG 2.1)
• Developed a product vision that combines digital accessibility, user-centered UX, and conversion optimization for the booking journey
• Cross-stream release management and quality assurance across the entire web and app area, including go/no-go decisions, rollout, and user acceptance tests
• Coordinated and prioritized with Legal, Compliance, external BFSG consultants, UX, Development, Marketing, and Management
• Conducted user research as well as usability and accessibility tests (including screen readers and keyboard navigation) and prototyping with UX/UI
• Defined KPIs to measure accessibility, conversion, and user guidance
• BFSG pilot journey “Search and Book” successfully delivered: first accessible features rolled out and the foundation for a long-term BFSG-compliant booking journey established
• Established sustainable process integration through close collaboration with consulting partners and internal teams

Development and Implementation

• Conceptualization and implementation of the various requirements.
• Experience and ability to collaborate with other delivery teams
• Lead a team of 15 people taking care of matters including monitoring operations, delegating tasks and managing budgets.
• Act as product owner and represent the product vision, strategy and priorities in the area of production operations.
• Work closely with the members of the area including developers, analysts and QA to ensure the successful delivery of logistics features and improvements.
• Lead the process design and lead the build team for the SAP implementation (EU countries) and post-merger integration in SAP PP, QM, MM, APO and SD modules.
• Implemented and optimized MRP Live (MD01N) for multiple plants, improving planning runtime
• Worked with business users to transition from classic MRP to MRP Live
• Implemented SAP QM module, including quality planning and inspection lot processing, resulting in a 20% improvement in product quality compliance.
• Developed and tested custom reports using SAP Query and ABAP for MES data analytics, improving visibility into yield rates and resource utilization.
• Translate production requirements into clear and actionable user stories, acceptance criteria and technical specifications.
• Skilled in discrete, and process/manufacturing (PP-PI) environments; deep understanding of master data, production & process orders, recipe management, batch management, capacity & scheduling, shop floor control, and integration with QM, MM, EWM, MES.
• Worked in Variant configuration (VC)
• Supported international rollouts and transformation projects for SAP PP, QM, PPDS, aATP, EWM, and Variant Configuration within a global strategy.
• Tested functionalities for various business scenarios include interface systems
• Involved in SIT and UAT and cutover activities

Technology: Project Management, SAP PP, QM, MM, APO, ABAP OO, HANA Modelling, FIORI, SAP UI5, AMDP, SAP SD, SAP FICO and S4 HANA Emedded analytics

• Developing methods for monocular 3D facial reconstruction and personalized geometric modelling from mobile imagery
• Building learning-based approaches for facial shape estimation, video-based facial analysis, and privacy-preserving visual learning

• IT training in theory and practice for IT specialists in application development and system integration