.NET MAUI Experts in Germany

AI Platform Backend – Senior Developer

Brought in to design and build a backend for an AI platform from scratch, including multi-provider LLM orchestration and real-time infrastructure for AI influencer personas at scale.

Tasks and responsibilities

• Architecture and implementation of 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 single interface.
• Design and development of a backend from scratch in C# / .NET 10, including domain modeling with DDD, a versioned RESTful API layer, and cloud infrastructure setup on Azure.
• Built a real-time chat infrastructure with Server-Sent Events (SSE), message persistence, and delivery guarantees for live operation of AI influencer personas at scale.
• Developed a media management service with integration of cloud object storage for upload and retrieval of influencer-generated content.
• Created an integration and unit test suite with data seeding for reliable regression testing across all core platform flows, significantly reducing production error rates.

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

• AI Integration (LLM & RAG): Design and build of an internal intelligent RAG system (Retrieval-Augmented Generation) based on LLMs, n8n, and vector data for the automated analysis of technical documents and error logs.
• Design & Implementation: Design of a robust RS-232/UART communication interface for an SBC-based embedded device to control medical shaker systems.
• Architecture & Protocol Design: Implementation of a highly maintainable software structure (OOP, SOLID) and definition of hardware-close, resilient communication protocols including multithreading and advanced error handling.
• Quality Assurance & DevOps: Test automation using xUnit, integration tests directly on the hardware target, and maintenance of technical documentation according 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

• 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).

• 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.

Enhancement and modernization of a mature Aspire backend application in the environment of a utility company, focusing on new business requirements, testing, legacy code cleanup, and stable backend delivery.

Core contributions & results Implemented new business requirements in the context of customer orders, subcontractors, and cross-company backend processes, and ensured consistent workflows in a distributed system landscape. Modernized existing backend components step by step 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 automations and integration processes via microservices, messaging, and API-based communication. Took over source code from external firms, systematically checked 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 alignment 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

• 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

• Software development with C#

• IT infrastructure development and maintenance with Microsoft Azure

• Integration of third-party systems

• Plan and set up DevOps CI/CD processes

• C# (.NET 8)

• Azure cloud services

• DevOps

• Jira

• Dynamics

• OData

• API management

• Key Vaults

• Service Bus

• Azure Functions

• Blazor

• Developed an app for store management
• Technologies: C#/XAML, Xamarin.Forms, MvvmCross, NUnit, Xamarin.UITest, Entity Framework Core, ASP.NET Core Web API, Azure DevOps, Visual Studio App Center

• Development of a tool for data entry, analysis, and transmission
• Conception, architecture, implementation, interface development, deployment
• App development (Android, iOS, Windows)
• Language: C#, .NET MAUI

• C# development in .NET 8.0
• Technical responsibility for architecture decisions (DDD, Clean Architecture, microservices)
• Introduction and systematic evaluation of GitHub Copilot, analyzing efficiency benefits, identifying suitable use cases, assessing code quality
• Developing best practices for using Copilot in the team, supporting rollout and coaching individual developers
• Conducting code reviews, architecture documentation according to Arc42
• Building stable CI/CD pipelines with Azure DevOps, introducing automated quality checks with SonarQube and .editorconfig
• Collaborating with stakeholders for continuous improvement of technical concepts
• Technologies used: Azure DevOps Server, Git, SonarQube, Visual Studio 2022, Sparx EA 17, Nagios LS, Nagios XI, C#, ReSharper 2.24.3, Clean Architecture, DDD, EF Core, Arc24, microservices, Angular, MediatR, SignalR, Copilot, OpenAI