Robotics Experts in Germany

• Industries: Energy, Telecommunications, Manufacturing
• Transformation & Change: Supported complex IT and digital transformation programs as Scrum Master, Agile Coach, Change Manager and RTE Consultant at Siemens Energy (global SAFe rollout), E.ON (sales technology platform), Schneider Electric (S/4HANA transformation DACH) and Vodafone (Operational Excellence)
• Agile Roles: Scrum Master, Agile Coach, Product Owner, Business Analyst, RTE Consultant in cross-functional and scaled teams (SAFe, Scrum, Spotify Model)
• Procurement Excellence: Strategic purchasing consulting with a focus on cost optimization, supplier management, digitalization and organizational development, including building supplier scorecard models, AI-supported procurement approaches and process automation in purchasing
• Managed functional leadership of interdisciplinary project teams of up to 12 people in national and international settings
• Successful launch of several global ARTs at Siemens Energy with improved coordination across sites
• Increased change acceptance and established communication structures in the S/4HANA program at Schneider Electric
• Introduced agile methods, OKR frameworks and KPI dashboards at E.ON, increasing velocity and transparency
• Reduced purchasing costs through strategic sourcing and supplier optimization
• Implemented process innovations in close cooperation with IT and business teams

In this project, I was responsible for the design and implementation of a new, modular, and highly scalable test bench platform for an automotive supplier. My focus was on developing a robust system architecture and programming the associated software, with consistent use of UML modeling throughout. This structured approach made it possible to greatly increase the reusability of individual LabVIEW test modules and to significantly reduce development time for follow-up projects. I also integrated modern automotive standards such as CAN FD, LIN, and safety requirements, which made the solution future-proof.

Technologies: LabVIEW, Visio, UML, CAN FD, LIN, DMM, Safety, image processing, project management, HMI, C#, C++, Python, Rust, CI

• Own full-stack development of an AI-native enterprise platform built on TypeScript, React, Vite, tRPC, Hono, and PostgreSQL, delivering AI-powered consulting workflows to B2B clients.
• Designed and shipped a multi-agent AI system using ReAct framework and Claude skills-style workflow patterns, including an intelligent PM assistant with rich system prompts, slash commands, tool integrations, and streaming chat UI.
• Architected an LLM evaluation framework: rubric-based LLM-as-judge, golden datasets, regression testing, and automated quality gating — ensuring consistent AI output quality at scale.
• Integrated LangFuse for end-to-end LLM tracing, conversation replays, and evaluation pipelines, enabling data-driven prompt optimisation that reduced token costs and response variance.
• Built with Drizzle ORM, pgvector, and knowledge graphs for structured data access, semantic search, and relationship-aware AI reasoning across the platform.
• Led TanStack React Query migration across the application — replacing manual state management with centralised caching and automatic refetching, reducing data-fetching boilerplate significantly.
• Practiced AI-native development throughout: Claude Code, Codex, Perplexity SDK, and LLM-assisted testing across the full development lifecycle. Deployed on Vercel + Azure ACA with Biome for linting/formatting.

• Capture and analyze stakeholder needs to define clear requirements and make sure the new website meets user expectations.
• Took on the role of Product Owner to lead the development team, set priorities, and monitor implementation progress.
• Coordinated the implementation of Optimizely as the new CMS, including adapting and integrating all required features to ensure a smooth user flow.
• Ensured the successful integration of features within the Condor lifecycle, such as flight booking, check-in, and other relevant services, to create a complete user experience.
• Actively communicated with stakeholders to gather feedback and make adjustments during the development process, continuously improving the user experience.
• Planned and carried out tests to ensure the quality of the implemented features and that all requirements were met.
• Methods used: Agile methods, SCRUM, SAFe
• Tools used: Optimizely, Jira, Confluence
• Result: Significant improvement in user experience, optimized booking and check-in processes, and a stronger digital presence for Condor in the market.

PSA, Peugeot Citroën, France (10/2023 – 05/2024)

• Launch Manager for electrode production rolling lines
• Setup, modernization, and commissioning of cleanroom production equipment
• Management of a team of 15 Chinese technicians
• Recovery of a three-month delay and on-schedule delivery

• Delivered MVP-focused full-stack architecture for a health-sector client: Vite/React frontend, backend services on Google Cloud Run, and Supabase for database plus IAM/authentication.
• Supported product requirements engineering and prioritized cost-aware workload placement, implementing browser-side/edge computation where feasible before moving logic to backend services.

• Developing global ACM Copilot services and shaping their evolution on a global scale
• Evangelizing the benefits and capabilities of Copilot to internal and external audiences
• Onboarding, mentoring, and training new ACM colleagues in services and methodologies
• Acting as point of contact for internal Copilot proof of concept adoption and change management
• Leading Copilot adoption strategy, communicating benefits, usage and ethical considerations
• Organizing events and workshops and fostering an interactive community to share updates, findings and best practices

• Developed a real-time video analytics proof-of-concept for deployment on NVIDIA Jetson edge devices.
• Implemented DeepStream pipelines including object detection, tracking, human pose estimation, face anonymization, and zone intrusion detection.
• Built a Qt/Python demonstration UI interfacing with the AI pipeline via REST APIs.

• CIO at nutrition R&D and producer (family owned)

Strengthened IT Team, recovered IT service, reviewed and streamlined complex SAP landscape, reviewed IT security set-up, reviewed laboratory IT

• Led strategic software development of fusion algorithms for precise object tracking, trajectory prediction, and environment modeling based on multimodal sensor data (e.g., camera, LiDAR, radar, GNSS, IMU)
• Developed and implemented navigation algorithms for autonomous vehicles, including path planning, obstacle avoidance, and sensor fusion of visual, inertial, and distance-based sensor sources
• Automated extraction and training processes with CI/CD
• Developed and optimized data pipelines and processes in Microsoft Azure using Apache Spark, Databricks, and PySpark
• Developed and optimized embedded software for automotive control units
• Designed latency-critical software for real-time control in robotic systems with RTOS (freeRTOS, SAFERTOS)
• Used the Vector toolchain (CANdela, DaVinci, CANoe) for configuration and diagnostics
• Optimized existing data pipelines and processes (ETL, data warehouse, SQL)
• Developed and trained machine learning models using PyTorch
• Created deep-learning-based object detection and visual SLAM algorithms, trained on combined data from camera, LiDAR, and IMU sensors
• Implemented computer vision algorithms for object detection and classification in robotic systems using OpenCV and YOLO, utilizing synchronized image and depth data
• Implemented behavior-based control systems for autonomous robots using ROS2 Behavior Trees
• Performed testing, release, and integration of sensor fusion algorithms into automotive production programs
• Ensured adherence to proper software development processes and safety standards to guarantee high data quality (MISRA, ISO 26262, ASPICE)

UEF 3.0 · Semantic Government Overlay (SGO) · Autonomous Systems (UAS / dual use)

• Designed: Semantic Government Overlay (SGO) – AI-guided administration without replacing existing specialist procedures. Read-only semantic layer over registers and specialist processes based on the Federal Information Management (FIM). Decision authority remains with the case worker (architecture principle).
• Developed: Reference architecture with source-backed, derived statements (Executable Ontologies OWL/RDF/SHACL). Technically guaranteed purpose limitation and no-write-path principle in specialist data – auditable, without a central data pool.
• Anchored: Regulation as a design principle: EU AI Act (high-risk obligations for public-sector AI, fundamental rights impact assessment under Art. 27), GDPR, NIS2, and administrative automation limits (§ 35a VwVfG, § 31a SGB X) as technical control points in the architecture.
• Created: Methodical tool for pilot organizations: data pipeline assessment (phase 0), compliance blueprint, and management summary as a decision-ready package for public administration.
• Specified: UEF 3.0 as a successor architecture to TOGAF – decision paper, canonical ontology, six-layer architecture, read/actuate boundary, federation registry, terminology concordance, and release delta as a closed specification status.
• Architected: AI-native mission OS for autonomous UAS and ground robotics as a tactical layer on top of a separately approved autopilot. Run-time assurance according to ASTM F3269-21 (Simplex pattern): the verified safety controller keeps authority, the AI function provides suggestions.
• Designed: Three-tier architecture – Tier 0 autopilot with 650 Hz flight control on RTOS, Tier 1 AI OS with semantic world model and multi-agent cluster, Tier 2 swarm and ground mesh. Zenoh as the primary fabric, MAVLink as the only authenticated command path (single writer). Result: graceful degradation – loss of the mission, not of the aircraft.
• Secured: Two-gate chain on the read/actuate boundary – governance gate (can-question: AI Act risk class per actuation, enforced human oversight under Art. 14, immutable log) before the RTA safety monitor (is-it-correct question: flight envelope, geofence, energy reserve) with revert to the baseline controller.
• Anchored: Dual-use architecture with common core and build-time fork instead of runtime switch. Three separate legal levels: civil variant – UAS under the EASA Basic Regulation (EU) 2018/1139 with the limited applicability under Art. 2(2) of the AI Act, ground robotics under the Machinery Regulation 2023/1230 with the full high-risk obligation chain, Cyber Resilience Act for both; unarmed carrier variant as defense material under AWG/AWV and Dual-Use Regulation 2021/821 (BAFA approval); armed variant under KrWaffKontrG. Each variant lives under exactly one dominant legal regime. Evidence base: AI BOM, SBOM, and complete data lineage.
• Analyzed: System analysis and realignment of grown engineering system landscapes. Approach concept for consolidation without migration – semantic layer over the existing sources instead of data transfer. Result: decision-ready implementation concept including an evaluation model for the target architecture.

• Developed an evaluation framework for AI-generated multiview driving videos intended for perception and embodied-AI/VLA-related training workflows.
• Designed automated checks for temporal coherence, cross-camera consistency, semantic correctness, and multiview geometric quality, exposing failure modes relevant to autonomous systems.
• Combined classical computer vision, learned visual representations, and vision-language models to convert complex video artifacts into measurable engineering signals.
• Built repeatable benchmarking and failure-analysis workflows to support model comparison, data-quality decisions, and system-improvement discussions.

• 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

• Leading technical purchasing with 4 employees
• Tendering, negotiating, and closing the gas supply for 2025 / 2026 and 2027
• Electricity purchasing for 2024 and 2025
• Feasibility analysis of a photovoltaic system for the sites Rinteln, Dodow, and Waibstadt, including tendering and negotiating possible partners
• Purchasing fossil fuels: diesel, gas, and electricity as well as CO2 certificates
• Purchasing industrial gases including CO2
• New setup in the area of cleaning and disinfecting agents for 3 plant sites and optimizing the stock handling of these hazardous substances
• Profitability calculation for the gas turbine (steam and electricity)
• Fleet concept: conventional drive vs. e-mobility
• Purchasing 29 new tractor units
• Two major maintenance projects: renewal of the outer shell of a high-bay warehouse as well as renewal of warehouse and high-bay warehouse logistics hardware and software
• Negotiating framework, maintenance, and consignment stock contracts including Capex and MRO with the four main machine suppliers
• Supporting performance issues during the commissioning of a new machine
• Negotiating and closing the contract for the conversion of three machines for the site in Spain
• Savings in the seven-figure range
• Return on Interim Manager (RoIM): factor 4.7