Python Experts in Germany

Creation of concepts for M365 implementation, especially Tenants, EntraID, EntraConnect and ExchangeOnline, taking BAS standards into account (mandatory baseline security requirements) in the project "Concept M365" with the aim of transferring the concepts to the M365 environments of Bitmarck and then handing them over to the customer.

• Creation of a current-state analysis of the existing M365 environments as well as the on-premises environments and the BAS standards.
• Creation of concepts for the topics Tenants, EntraID, EntraConnect and ExchangeOnline taking the BAS standards into account
• Design and implementation of an automated solution for creating standardized M365 tenants based on Microsoft M365 DSC (Desired State Configuration)
• Transfer of the concepts into the M365 environments
• Creation of detailed technical documentation

Stabilizing an Azure/.NET landscape in live operation.

• Architecture, DevOps, and operational readiness; technical decisions under time pressure
• Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics

Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps

• Marketing Strategy: Lead the end-to-end analysis and evaluation of cross-channel marketing campaigns across the entire Customer Journey. My focus is identifying optimization potential and deriving clear, actionable recommendations that drive measurable business impact.
• Data Science & AI: Advanced predictive modeling (Churn, LTV), market basket analysis, clustering, and real-time AI-powered audience discovery utilizing RAG/LLMs.
• Marketing Analytics & Measurement: End-to-end attribution analysis, Marketing Mix Modeling (MMM), audience segmentation, conversion path analysis, and A/B testing across all major platforms.
• Data Engineering & Reporting: Designing and managing robust, multi-platform data pipelines (BigQuery, GCP) for data consolidation, automated dashboard generation, and critical API integrations.

• Development of a production-ready Enterprise AI solution for the automated processing of invoices and business documents
• Integration of Azure AI Document Intelligence and LLM technologies into existing business processes
• Development of robust REST APIs for automated document processing and system integration
• Extraction, validation, and storage of structured invoice data in Azure SQL as a base for analytics and machine learning models
• Development of an AI-based recommendation engine with machine learning and deep learning to generate personalized product recommendations based on historical purchase data
• Implementation of logging, monitoring, error handling, and validation mechanisms for stable production use
• Collaboration with business teams to define business rules and integrate the solution into existing enterprise processes

Technologies: Python, Azure AI Document Intelligence, Azure OpenAI, Azure SQL Database, REST APIs, Machine Learning, Deep Learning, OCR, Pandas, JSON, Workflow Automation

• Planning and concept development for building a new business model, including structuring and implementing business processes.
• Coordination and management of external service providers as well as interface management.
• Introduction and implementation of new digital tools and processes to optimize operational workflows.

• Development of cloud native applications to provide a multi-vendor marketplace for different digital assets (e.g. NFTs)
• Design and operation of a microservice architecture using Nest.js, MySQL, Redis, Hasura, Algolia, Docker and Serverless
• Design and operation of a streaming data architecture using Kafka (with JSON Schemas)
• Creation of CI/CD pipelines with GitHub Actions for automated deployment of applications
• Testing and evaluating new technologies for more stable, faster, safer and more sustainable application development
• Building the full infrastructure with Terraform in AWS
• Integration of Stripe to handle international payments
• Use of Algolia for real-time search of digital assets on the platform
• Presenting results to stakeholders and running internal meetups
• Federation of services with GraphQL and Hasura
• Discussions about architecture decisions in the IT landscape and their impact
• Use of message queues for app-internal communication and component encapsulation
• Advising internal staff on the implementation of business and technical requirements
• Test Driven Development: unit, integration and E2E testing using JUnit
• Use of Next.js/React with SASS/SCSS for frontend applications
• Use of Vue.js with SASS/SCSS for frontend applications
• Integration of security-related mechanisms (JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA, secret vaults)
• Creation of microfrontends using Retool for fast prototyping and testing of functionality
• Use of nx monorepo with nrwl

Product:

• Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
• Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
• Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
• Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
• Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.

Agent Orchestration & RAG Systems

• Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
• Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.

• Led the hardware development and validation of a safety-critical 400 V battery management system (BMS) for the TOGG SUV program; performed system architecture reviews, schematic validations, EMC and reliability tests, and root cause analyses in line with relevant automotive standards (ECE-R10, CISPR25, ISO-26262). Coordinated cross-border EU engineering teams, customer reviews, and technical documentation to deliver a production-ready, validated system.

• Architected and integrated 22 state-of-the-art ADAS validation vehicles for BMW ADCAM and LIDAR programs at Magna Electronics; synchronized up to 26 heterogeneous sensors (LIDAR, RADAR, cameras, GNSS/INS) using PTP-based timing architectures. Defined the system architecture, HW/SW interfaces for hardware-in-the-loop (HIL) reprocessing, sensor integration strategies, and data acquisition frameworks. This enabled scalable vehicle-level validation, improved validation efficiency by 25%, and reduced project costs by €1.45 million.

• End-to-end validation and integration of automotive radar platforms for a Daimler project at Continental. Developed automated open-loop hardware-in-the-loop (HIL) environments to accurately test target tracking KPIs, field of view limits, and thermal and voltage-related ECU state machines. Used a highly complex toolchain consisting of CANoe, Lauterbach Trace32, RADAR target simulators, and EMC shielding chambers for RF and system validation. Synchronized global, interdisciplinary teams to speed up troubleshooting and close critical technical gaps.

• Reconstructed and validated the product architecture of an electromechanical e-bike by integrating and troubleshooting critical subsystems (BMS, motor control, sensors, HMI, electronic locking systems). Built a comprehensive system-level test bench for functional testing, fault reproduction, and performance analysis; coordinated suppliers and implemented corrective actions to improve reliability and traceability.

• Defined the system architecture and validation strategy for a LIDAR platform developed in cooperation with Elmos Semiconductor; evaluated optical measurement concepts, SPAD detector integration, and system requirements, and created technical recommendations for product development and verification.

• Developed LabVIEW-based automation and verification software for a high-precision hydraulic and electromechanical test system for FTE Automotive; integrated NI DAQ hardware for high-frequency real-time capture of physical measurement data. Developed automated test sequences, programmable endurance tests, troubleshooting routines, data logging, and analysis tools to improve test efficiency and traceability.

• Successfully managed complete engineering life cycles for well-known industrial customers (Magna, Continental, Farasis, FTE Automotive, BMW, Daimler, TOGG) – from requirements engineering and proof of concept through system integration and validation to technical documentation, supplier coordination, and user training.

AI telephone assistant platform

Claude Code, Google AI Studio, Python, LLM / Voice-AI, PostgreSQL

• Conception and hands-on development of an AI-supported telephone assistant platform (voice AI / LLM) – from idea and architecture to MVP/product.
• Built agentic workflows and full automations with Claude Code and Google AI Studio.
• Also delivered AI-supported work in client engagements: used Claude Code for governance documentation, requirement drafts, and automations.

• Task Engineering: Evaluating Coding Agents.
• Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
• Prompting & Translation: finding failure points where AI does not work, in German.
• Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
• Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
• Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
• Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.

Digitizing real-world places with 3D/LiDAR scans to make spatial data usable for AI applications and to derive concrete use cases and prototypes from it.

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

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

Most mid-sized companies already have their numbers. What is missing is the translation: a dashboard with forty tiles does not answer a single question that is actually asked in management.

Analysis

• Evaluation of existing data with Python and SQL
• Checking data quality and methodology before making a statement
• The result is an analysis that leads toward a concrete decision

Preparation

• Reports in Power BI and Tableau
• Interactive calculators and visualizations on the web
• Presentations and specialist texts for customers, sales and the public
• Analysis and communication from one source — that

• Analysis of the existing CAN communication between microcontrollers
• Analysis of the sensors used and the measured values collected
• Planning the CAN messages for transmitting the measured values
• Iterative adjustment of the microcontroller code to the new CAN messages
• Cross-compilation from x64 to arm64

Project: Process optimization & IT support in an insurance broker office.

Project activities:

• Analysis of processes and definition of requirements
• Consulting for the implementation of a cloud solution (soho)
• Installation and verification of new infrastructure HW
• Cloud installation & configuration
• Definition and creation of use cases
• Performing user acceptance tests (UAT)
• User training / training
• IT support (cloud, PC, server, printer, network)

Label: Insurance, infrastructure, configuration, training, support