Azure App Service Experts in Germany

Development and further development of an internal platform for managing and providing technical resources, virtual machines, and infrastructure services. The platform supports self-service processes and covers functions that are conceptually comparable to cloud management solutions like Azure or AWS.

• Responsible involvement in the design, development, and implementation of new backend and frontend features
• Hands-on development with Java, Spring Boot, Python, and Angular
• Implementation of REST interfaces, business logic, validations, and integrations into existing system landscapes
• Further development of modern web interfaces with Angular, including connection to backend services
• Participation in architecture and design decisions within the team, especially with regard to scalability, maintainability, and clean interfaces
• Containerization and deployment of applications with Docker, Kubernetes, and Helm
• Support with CI/CD processes and deployment to Kubernetes-based environments
• Work in the environment of vSphere, Broadcom, GitLab CI/CD, ArgoCD, Maven, npm, and NuGet
• Close collaboration with developers, business teams, DevOps, and other technical stakeholders
• Analysis of technical requirements, deriving suitable solutions, and independent implementation in an agile team
• Use of GitHub Copilot to support code generation, refactoring, test case creation, and technical documentation

Methods/ tools/ technologies: Languages & frameworks: Java (21), Spring Boot (4.x), Python, Angular, Robot Framework, Kubernetes, Helm Persistence: PostgreSQL, MongoDB, Hibernate, Liquibase Architecture & communication: REST, gRPC, GraphQL, Apache Kafka, OpenAPI, Microservices, Event Driven, Domain Driven Design Cloud & infrastructure: Terraform, Docker, Rancher, Helm, Ansible Security: OAuth2, MS (Entra ID), web security, Keycloak (extensions for detailed group rights) DevOps: GitLab CI/CD, Ansible, Maven, Gradle, Grafana, Prometheus, Git, GitHub Copilot Testing & QM: JUnit, Robot Framework, automated component and integration tests, E2E tests with Playwright, Testcontainers, EasyMock Methodology & approach: Kanban, JIRA, Confluence, Clean Code

• 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

• 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

Task:

• Design and build a proof of concept (PoC) for a future-proof virtualization platform, taking secure system architectures into account
• Assess the current state of existing infrastructures and develop selection and evaluation criteria for the right OS virtualization platform
• Carry out the requirements analysis and then create and prioritize tickets in the ticket system
• Complete and continuously update a tool evaluation matrix based on PoC results
• Support team knowledge building through clear documentation of the approach and results in Confluence
• Enterprise analysis of existing hardware (creating different BoMs)

Technologies: Vmware, Vmware Aria Operations, Osism, Canonical OpenStack, FishOs, Linux, Terraform, Ansible, Confluence, Alma

Development of an iOS app for virtual try-on and outfit suggestions

The goal of the project is to develop a mobile application for personalized, photorealistic outfit suggestions. Users should be able to upload their own photos, try on clothes virtually, and find products that can be bought directly in the generated suggestions.

• Planning and implementation of the onboarding and photo upload in the iOS app
• Development of the mobile application with Expo and React Native
• Implementation of a Hono/Node.js backend for user, product, and generation processes
• Building an asynchronous processing pipeline with BullMQ and Redis
• Connection of PostgreSQL/pgvector and S3 for product, image, and generation data
• Integration of Gemini and OpenAI for outfit generation and image processing
• Implementation of a credit system and integration of RevenueCat
• Integration of Stripe Connect and affiliate product feeds for products that can be bought directly

Label: TypeScript, React Native, Expo, Hono, Node.js, PostgreSQL/pgvector, BullMQ, Redis, S3, Gemini, OpenAI, RevenueCat, Stripe Connect, Docker

• Applied modern JavaScript features, including ES6+ syntax, destructuring, modules, array methods, and asynchronous programming, to develop efficient and readable frontend code.
• Implemented frontend integration patterns for PHP and Laravel backend services, connecting React interfaces to REST APIs and handling structured JSON data.
• Developed interactive, functional component-based frontend applications using React Hooks, JavaScript, and TypeScript, alongside backend applications and RESTful APIs using Python, Django, Flask, and FastAPI, focusing on reusable components, modular architecture, maintainability, and efficient data processing.
• Maintained a dynamic portfolio platform using PHP, Laravel, Livewire, and MySQL, implementing end-to-end functionality across frontend interfaces, backend services, and database operations.
• Validated server-side request handling, routing, middleware, and form validation using Laravel features to support reliable application workflows and consistent data processing.
• Designed and managed relational database structures using MySQL and Laravel Eloquent ORM, implementing data models, relationships, database migrations, and efficient queries for content management.
• AI-powered applications integrating Large Language Models (LLMs) through external APIs and locally hosted models, exploring practical use cases for conversational AI, intelligent automation, and AI-assisted workflows.
• Built local AI applications and developer tools for running, configuring, and interacting with locally hosted language models, gaining experience with local inference, model integration, and privacy-conscious AI workflows.
• Explored Retrieval-Augmented Generation (RAG) approaches to combine language models with external knowledge sources, enabling context-aware responses based on relevant application data and retrieved information.
• Integrated AI services with backend APIs and application components, developing reusable modules for model communication, response processing, error handling, and data exchange.

• 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

• Supporting several agile teams in the new product development of an enterprise CRM and ERP application
• Web frontend development with Angular 17–21 (microfrontends, Domain-Driven Design, MDB-Bootstrap)
• Backend development with C# and .NET 7–10, MongoDB, MassTransit, RabbitMQ, Entity Framework Core, ElasticSearch (microservices, DDD)
• Technical feature design for assigned tasks
• Technical architecture design including forward-looking planning of AI-supported extension options
• Proof-of-concept implementation of AI-supported workflows with n8n and a locally hosted LLM (Ollama)
• Coordination with stakeholders and Product Owners, support with sprint planning

Result: Delivery of production-ready microservices and frontend modules in agile sprint cycles.

Environment: .NET 7–10 · Angular 17–21 · C# · TypeScript · OpenAPI · Microfrontends · DDD · Kubernetes · Docker · Helm · MS SQL Server · PostgreSQL · MongoDB · MassTransit · RabbitMQ · EF Core · ElasticSearch · Kibana · Azure DevOps · KeyCloak · n8n · Ollama

• Software development
• Technical design of software architecture and design (considering functional and non-functional requirements)
• Frontend and Backend
• Refactorings
• Code reviews
• Unit tests
• Automated integration tests
• E2E tests

Global Identity Services (GIS) is the identity provider for the Digital Services Platform (DSP). GIS is responsible for authenticating and authorizing end users and other DSP services by issuing security tokens. This includes:

• Identity management (e.g., user registration, password reset and change, user profiles)
• Management of roles and permissions
• Single Sign-On (SSO) across DSP services
• Management of OAuth resources and terms and conditions

• Led and coordinated consumption and price calculations for gas and electricity forecasts to ensure accurate and reliable price determination
• Implemented modern .NET 7-based microservices and Web APIs in an Azure environment using Azure App Service, Azure Storage and Azure Service Bus
• Created and managed infrastructure in Azure using Terraform, including resource provisioning and the automation of deployment processes
• Developed and maintained Azure DevOps pipelines to optimize build, test and release workflows
• Optimized data management with SQL Server and ensured seamless integration across all services
• Developed the frontend with Angular 16, TypeScript, CSS, HTML and Kendo UI to provide an intuitive and engaging user interface

• New development of project room functions
• Connection of REST API of a self-developed web service (.NET 7/8) as Azure App Service
• UI tests with Playwright
• Extension of Azure DevOps pipelines
• Migration to Azure SQL Server
• Software / technology: SharePoint Online, PowerShell scripts, SharePoint Framework, MobX, C#, Logic Apps, Playwright, Azure SQL Server, Graph API

• Automatic creation of reports based on log data from the Senstar surveillance camera software regarding access times for various camera systems
• Gathering requirements and translating them into a suitable technological solution
• Implementation of Python scripts to read, process, and convert Senstar log data into PDF reports
• Reading configuration files to control the scripts
• Packaging the Python scripts and all dependencies as an executable cmd. Offline installation on Windows Server
• Providing –help parameters to list and explain the script parameters
• Creation of documentation for installing, configuring, and operating the scripts
• Technical environment: Python 3, SQL, Senstar, Windows Server, Python Setuptools, fpdf

• Further development and partial new development of a distributed cloud application for providing data in energy trading
• Independent implementation of the infrastructure (IaC)
• Creation of automated CI/CD pipelines, containers, REST APIs, and Lambdas
• Continuous cost and performance optimization
• Collaboration in an international Scrum team and with experts in energy trading
• Technologies: C#/ASP.NET Core; EF Core; PostgreSQL; Terraform/AWS CloudFormation; HTTP; REST/Web API; Swagger/OpenAPI; Azure DevOps; Rider; VS Code; git; Docker; AWS (S3, EC2, Fargate, Lambda, Step Functions, Secrets Manager, VPCs, ALB/NLB, RDS, Cloudwatch, AWS CLI, Amazon MQ); Redis; OAuth; OpenID Connect
• Languages: C#; TypeScript; HCL; Docker; Bash; PowerShell; YML; JSON

• 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