MVC Experts in Dusseldorf

• Analysis and remediation of security vulnerabilities in a risk assessment system for energy trading
• System analysis
• Threat modeling
• Decision-making on vulnerability mitigation strategies
• Implementation of vulnerability detection mechanisms
• Security scans
• DevSecOps practices
• Technical environment: Visual Studio Code, JetBrains Suite, MS Threat Modeling Tool, DevSecOps, Git, AWS, DynamoDB, SQL Server, Endur, Snowflake, Orca
• Languages: C#, JavaScript, TypeScript, Python, PowerShell, Bash, Terraform, SQL

• 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

• Contributed to the development of an advanced RAG AI Chat application that integrates multiple LLM models, enabling users to seamlessly switch between models based on specific tasks. This improved the user experience by providing tailored, efficient solutions for various use cases, such as event scheduling, booking systems, and complex task management.
• Participated in designing and implementing a robust backend architecture using Spring AI, enabling advanced AI-driven capabilities like intelligent task automation, language processing, and contextual recommendations. Leveraged Spring AI Tools and Advisors to enhance the performance and decision-making of the AI models.
• Collaborated on the integration of vector databases to support embeddings, enhancing the app's ability to understand user queries and perform actions based on complex, real-time data inputs.
• Contributed to the development of a seamless, user-friendly front-end interface using React with TypeScript support, ensuring a modern, responsive, and scalable user experience across platforms.
• Assisted in implementing state management with Redux RTK for efficient data flow and real-time updates, optimizing the overall user experience in dynamic scenarios such as scheduling and task management.
• Partnered with stakeholders to define feature requirements, helping ensure that the app could scale to meet evolving business needs and integrate with other systems like calendar and email services. Worked alongside cross-functional teams, including data scientists and UI/UX designers, to fine-tune AI models and ensure alignment with project goals.
• Contributed to ensuring end-to-end system performance, security, and compliance by helping integrate authentication mechanisms, role-based access control, and secure communication protocols in both backend and frontend layers.

Technology Stack and Key Contributions:

• Java / Spring Boot / Spring AI: Developed backend services leveraging Spring AI for intelligent responses, task automation, and complex workflows.
• React / TypeScript: Built intuitive user interfaces with React and TypeScript, ensuring a smooth and scalable frontend.
• Redux RTK: Managed application state with Redux RTK for optimized state management, enabling dynamic, real-time data updates.
• Vector Databases: Integrated vector databases (pgVector) for embedding support, improving AI model performance in handling complex queries.
• PostgreSQL / Redis: Managed persistent and temporary data with relational and in-memory data stores, ensuring data integrity and speed.
• Kafka: Utilized Apache Kafka for event-driven communication and seamless integration between microservices.
• Spring Security: Ensured the security of backend services with robust authentication and authorization mechanisms.
• CI/CD & DevOps: Integrated continuous integration and deployment pipelines to ensure rapid and secure deployment of features and updates.

• Redesign of the “Hessian Platform for Migration and Refugees”
• Technologies: C#, .NET 8.0, ASP.NET WebAPI, Blazor
• Architecture principles: Domain Driven Design, Mediator Pattern, Outbox Pattern, IOSP, Clean Code
• Methodologies: SCRUM, coaching, team lead

• Built and launched the AI-powered “E-Invoice Corrector,” an intelligent system for validating and correcting invoices, using Python, FastAPI, and machine learning. The system is now live at Fintom8.
• Converted the Corrector into a fully functional API, published with Swagger documentation for easy access and integration by internal and external consumers.
• Designed, experimented with, and optimized advanced LLM prompts and meta-prompting strategies to improve automated reasoning, error correction, and decision-making in agent workflows.
• Wrapped and integrated existing APIs within the Google Agent Development Kit (ADK) framework to enhance automation capabilities and conversational AI workflows.
• Implemented comprehensive unit testing using pytest and unittest, and employed breakpoint debugging (VS Code, pdb) to ensure code reliability, maintainability, and smooth runtime execution.
• Utilized Pydantic and Tabulate for structured data validation, API schema management, and clear tabular data representation in testing and debugging workflows.
• Pursuing the Google Cloud Professional Certificate.

• Visualization, search, and maintenance of various types of master data, providing them via a REST API, and implementing a variety of import and export formats.

• Implementation, architecture, project management.

• Technologies and tools: Angular (Signals, Signal Store, swagger-codegen, standalone components), Java, PostgreSQL, ActiveMQ, JavaScript, Spring Boot (Spring Core, Spring MVC, Spring Data/JPA via Hibernate, Spring Security, Spring Modulith), JUnit, Flyway, QueryDSL, GraphQL, REST API, Node, npm, Maven, SonarQube, GitLab CI/CD pipelines, Docker, Nexus, OpenAPI + Swagger UI, Keycloak, OAuth2, OpenID Connect, IntelliJ IDEA, Jira, Confluence.