.NET MAUI Experts in Germany

• AI Integration (LLM & RAG): Designed and built an internal intelligent RAG system (Retrieval-Augmented Generation) based on LLMs, n8n, and vector data to automatically analyze technical documents and error logs.
• Design & Implementation: Designed a robust RS-232/UART communication interface for an SBC-based embedded device used to control medical shaker systems.
• Architecture & Protocol Design: Built a highly maintainable software structure (OOP, SOLID) and defined resilient, hardware-level communication protocols, including multithreading and advanced error handling.
• Quality Assurance & DevOps: Automated testing with xUnit, ran integration tests directly on the hardware target, and maintained technical documentation to strict medical technology standards via Azure DevOps.

Label: C#, .NET, LLMs, RAG, n8n, RS-232, UART, Multithreading, async/await, xUnit, gRPC/protobuf, Blazor, MudBlazor, EF Core, Visual Studio 2026, Azure DevOps

Gronic Ident & Sign

Core technologies: Android, Jetpack Compose, Retrofit, Regula Document Reader, Adobe Sign

Android app on dedicated devices for identifications and electronic signatures at the PoS

AI Platform Backend – Senior Developer

Hired to design and build an AI platform backend from the ground up, including multi-provider LLM orchestration and real-time infrastructure for AI influencer personas at scale.

Tasks and Responsibilities

• Architected and implemented a multi-LLM orchestration layer with Semantic Kernel to integrate GPT-4 and other providers for core platform logic and AI influencer personas, reducing model-switching overhead by abstracting provider APIs behind a unified interface.
• Designed and developed a backend from the ground up in C# / .NET 10, including domain modeling with DDD, a versioned RESTful API layer, and cloud infrastructure on Azure.
• Built real-time chat infrastructure with Server-Sent Events (SSE), message persistence, and delivery guarantees for running AI influencer personas live at scale.
• Developed a media management service with cloud object storage integration for uploading and retrieving influencer-generated content.
• Created an integration and unit test suite with data seeding for reliable regression testing across all core platform flows, significantly reducing the production error rate.

Tools and Technologies: C#, .NET, ASP.NET Core, Python, TypeScript, MySQL, Semantic Kernel, EF Core, Minimal APIs, LLM Orchestration, Prompt Engineering, Agentic AI, Generative AI, AI-Assisted Engineering, Claude Code, GitHub Copilot, Google Gemini, OpenAI API, Ollama, Redis, Azure, Azure Container Apps, Azure Database for MySQL, Docker, GitHub Actions, Clean Architecture, Vertical Slice Architecture, CQRS, Domain-Driven Design, REST API, xUnit, Integration Testing, Unit Testing, Jira, Confluence, Scrum

• Software development with C#

• IT infrastructure development and maintenance with Microsoft Azure

• Integration of 3rd-party systems

• Planning and setting up DevOps CI/CD processes

• C# (.net8)

• Azure Cloud Services

• DevOps

• Jira

• Dynamics

• Odata

• Api Management

• Key Vaults

• ServiceBus

• Azure Functions

• Blazor

• Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
• Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.

• Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
• Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
• Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
• Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
• Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
• Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
• Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
• Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
• Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
• Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
• Integration of RESTHeart to create a REST API for MongoDB.
• Build an Angular frontend to simplify data queries and master data maintenance.
• Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
• Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).

• Fixing issues in the program logic

• Covering the changes with unit tests

• Analyzing and documenting the data structure of the various applications

• Analyzing and documenting the parameters for configuring the applications

• Analyzing and documenting the measures required to ensure the operation of the applications

• Analyzing and designing the separation of the individual database structures

• Analyzing and estimating the effort for planned extensions

• Analyzing, maintaining and documenting a heterogeneous legacy system landscape for a print media service provider

• Technology: C#, VB.NET, C, Python, Microsoft SQL Server, Visual Studio 2010, JetBrains Rider, Visual Studio Code, arc42, Draw.io, Jira, GitLab

Further development and modernization of a mature Aspire backend application in the energy utility sector, focusing on new business requirements, testing, legacy code cleanup, and stable backend delivery.

Key Contributions & Results Implemented new business requirements in the context of customer orders, subcontractors, and cross-company backend processes, ensuring consistent workflows across a distributed system landscape. Gradually modernized existing backend components and reduced technical debt through targeted legacy code cleanup, refactoring, and structured code reviews. Improved the testability of business-critical services by expanding automated tests with xUnit, AutoFixture, and clearer validation structures. Supported the further development of workflow automation and integration processes through microservices, messaging, and API-based communication. Took over source code from external companies, systematically assessed code quality, and derived technical improvements for maintainability, stability, and integration. Worked in agile development processes with Jira, Confluence, and Azure DevOps and supported cross-team coordination on architecture, quality, and implementation. Technical Metrics Technologies & Methods C#, .NET, ASP.NET, ASP.NET Core, Aspire, Docker, RabbitMQ, gRPC, REST API, Swagger, Microservices, NServiceBus, AutoMapper, Autofac, xUnit, AutoFixture, FluentValidation, Entity Framework Core, MediatR, Redis, Consul, Serilog, SonarQube, Azure DevOps, Azure Monitor, GitLab, Google Protocol Buffers, IronPDF, Mailjet, Jira, Confluence, Miro, Agile Development, Scrum, Code Reviews, Refactoring, Legacy Code Cleanup, Workflow Automation, Power Grids

• Successfully implemented the complete macOS app 'PDF Content Search' and iOS app 'PDF Cnt Search' from initial concept through final deployment to the App Store.

• Strategic project development, realisation, and implementation with internal and/or external development team
• Multi stakeholder management
• Planning new projects, cost calculation, risk calculation
• AI project for the electrical components production
• Building management systems integrations (BACnet, Modbus, etc)
• Inhouse BACring system architecture and development (control system for fire protection and smoke extraction systems)
• Inhouse MES system architecture and development
• Project management
• Agile-SCRUM project development
• Solution architecture and processes analytics (UML)
• Business application development
• Jira project management
• Reporting and documentation
• Recruitment process for the IT staff
• Software architecture, project development, costs, risks
• Education IT staff (internal and external)
• Responsibility for 5 development/DevOps/QA teams

• Backend development: .Net 8, C#, PostgreSQL, Entity Framework Core, REST Web APIs, Docker, Kubernetes, Kafka, Open API Swagger, Apache Airflow, Resharper, Git, Microservices, SOAP, gRPC, Hangfire, OAuth 2, GraphQL
• Interface development for document processing with SmartFix, Softexpansion and Natif.ai: C#, REST API, Resharper, Git
• Deployment: Azure DevOps YAML, Vanilla Helmchart, Rancher, Kubernetes Cluster, Linux Docker, Windows VM, Python
• Unit tests and integration tests
• Telemetry, Kibana, Grafana, Elastic Search
• Work in a Kanban team of 8 developers, 1 tester and one Product Owner

• Responsible for the 5-head development team and Scrum + DevOps approach
• Designed and implemented the cloud architecture for the application landscape
• Lead development for the user management on Azure Cloud using .NET 8/C#
• Development for the user management frontend using React (TypeScript)
• Technologies: Azure AD, Functions, Storage, CosmosDB, Service Bus, AKS, Monitor, Pipelines, Key Vault, MSSQL, Bicep, App Service, Log Analytics, Application Insights, Cost Management
• Backend: .NET/C#; Frontend: Angular (TypeScript)
• Unit testing: NUnit, xUnit, Moq
• CI & CD: Azure DevOps, GitHub Actions, GitLab CI
• DevOps & IaC: Bicep, Terraform, Docker, Kubernetes
• Security & Compliance: ISO 27001, DevSecOps
• Software development approach: Scrum, SAFe, Kanban

• Development of Blazor-Server applications for data management
• Focus on unifying design and user experience
• Mentoring junior developers
• Establishing and consulting for coding guidelines and best practices
• Technologies: .NET 9, Blazor Server, MudBlazor, HTML, CSS, MS SQL Server (T-SQL, Views, Trigger, Stored Procedures, Table-Valued Functions), Entity Framework, Visual Studio, Scrum, agile, git

• Support in restructuring and designing the group's internal Android apps
• Defining essential modules and implementing accessible components
• Establishing agile approaches at an international level
• Technologies & Methods: Kotlin, Android, JUnit 5, Koin, Azure DevOps, Android Studio, Git, Jetpack Compose, Coil, Flow API, Ktor, Coroutines, TypeScript, Node.js