Kubernetes Experts in Dusseldorf

Sovereign, cloud-native developer platform based on Kubernetes for critical energy infrastructure; around 200 people and 15 product teams.

• Introduced the product operating model for the platform, aligning around 18 product managers and product owners with Platform Architecture and Delivery in a matrix organisation.
• Defined the platform product processes and core product artefacts as the standard across all product teams.
• Established processes for non-functional requirements and Requests for Enhancement from consuming teams and customers.
• Designed the Jira structure supporting the programme's product and delivery processes.

• Optimizing and accelera­tion of our Gitlab CI pipeline

• Conceptual work for the PoC of the Zero Trust system

• Extension of the policy-engine backend in Go

• Extension of the policy-testing mechanism in Python

• Architectural design of the PEP component of Zero Trust

• Documentation of the product

• Technologies: Zero Trust, Go, Python, Gitlab CI, Docker, JWT, Domain-Driven Design

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

• Training AI models, evaluating images and text UI/UX, turning the provided data into insights through OpenAI Feather as part of the machine learning workflow

Technologies: OpenAI Feather

• Led end-to-end delivery of ML/AI applications for the QuantistryLab simulation platform, from requirements definition and solution design to development, testing, deployment, and production support, coordinating efforts across back-end, DevOps, and ML teams
• Designed and implemented a compound search system with an open-weights LLM, the Pydantic AI agent framework, and the Model Context Protocol (MCP), exposing it through FastAPI endpoints
• Deployed and configured vLLM-based LLM serving on Kubernetes
• Built CI/CD pipelines and Helm charts to automate deployments across staging and production environments
• Instrumented the search system with OpenTelemetry spans and traces, integrating with the Honeycomb observability platform to monitor component-level latency and functional errors
• Developed a custom evaluation dataset and implemented evaluations for retrieval relevance, answer correctness, tool-call accuracy, and end-to-end task success
• Reduced infrared spectrum prediction time by 83% (from 60 to 10 minutes) by replacing a quantum-mechanical model with a pretrained graph neural network; fine-tuned the model using PyTorch, built and containerized the inference pipeline with Docker, and integrated it into the platform
• Implemented an MLflow model registry with MinIO-backed artifact storage
• Advised sales and science teams on ML/AI applications for prospective client projects, providing technical expertise to shape proposed solutions and prototypes

Technologies: AWS, Hetzner, Kubernetes, Helm, Docker, vLLM, Pydantic AI, MCP, Qwen, Llama 3, MLflow, MinIO, GitHub Actions, Python, FastAPI, OpenTelemetry, Honeycomb, PyTorch, Polars, pytest

• Supporting the DevOps team in Terraform-managed, multi-region AWS infrastructure to achieve environment parity.
• Developed end-to-end CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy, automating the build and deployment.
• Maintained pre- and post-deployment scripts to automate critical tasks such as database schema migrations and environment sanity checks.
• Implemented CI/CD flow specifically for hotfixes via separate Git branches, managing back-merge activities from feature branches to release branches to ensure code integrity through automated conflict resolution.
• Deployed a dedicated, lightweight sanity check application hosted cost-effectively on Azure Container Apps to run automated health and basic functional checks as a post-deployment activity triggered via pipeline.
• Investigated production incidents through code changes and AWS CloudWatch logs.
• Coordinated integration of Dynatrace APM and its APIs for monitoring purposes.
• Full stack QA strategist for a high-traffic e-commerce platform built on a layered architecture for the back-end testing of core platform services, especially the order management system in Zed and Glue layers.
• Managed automation activities, testing process, and refactoring practices.
• Responsible for framework migrations, setup, and training for new automation frameworks.
• Promoted a shift-left approach within the QA team and created the test concept.
• Participated in meetings with IT managers, business owners, product owners, and team members.
• Designed and implemented contract testing to validate API schema compatibility between the order management system and the Zed and Glue layers, reducing production-relevant breaking changes by approximately 3%.
• Led the migration to a multi-environment framework that enabled test execution across 4 country configurations from a single codebase.
• Integrated automated unit and functional tests directly into the GitLab CI/CD pipeline, reducing pipeline runtime by 32%.
• Coached and trained 5 QA engineers across Germany and Hungary in test automation, framework architecture, and best practices.
• Architected a layered backend test automation framework separating business logic, API request builders, and the database layer.
• Piloted AI-assisted testing with Playwright Agents, the Playwright MCP Server, and GitHub Copilot for automated test generation, execution, and self-healing Playwright scripts.

(Maternity/Parental Leave: July 2023 – Aug 2024)

• Domain: Payment Domain | Client: Telefonica Germany
• Project: General Payment Service

The General Payment Service is responsible for processing of online payments via external payment service provider like Safer pay and PayPal

• Developed Design of Use (DOU) and interface contract documentation, ensuring clarity and compliance across system integrations
• Designed and delivered REST/SOAP web services with Spring Boot and Spring Data JPA, publishing Swagger contracts through WSO2 API Gateway to improve accessibility and governance.
• Spearheaded the on-premises to AWS Cloud migration, re-platforming from Oracle to PostgreSQL on AWS RDS and deploying services on EC2, improving scalability and cost efficiency.
• Containerized microservices using Docker and orchestrated deployments with Kubernetes, streamlining deployment pipelines and improving system reliability.
• Implemented proactive monitoring and logging via AWS CloudWatch and Kibana, ensuring stability and performance during cutover.
• Enhanced collaboration through code reviews and peer reviews, promoting maintainability and clean coding standards.
• Strengthened quality by writing comprehensive JUnit tests and preparing detailed test cases enabling early defect detection
• Delivered automated API testing with Ready API, Postman, and SOAPUI, and conducted performance testing with JMeter, ensuring reliability in high-transaction environments.

• Creating interfaces between the legacy platform and the new container solution
• Coordinating required contributions from line units
• Moderating regular status meetings with the software vendor
• Minimally invasive conversion of TWS scheduling from the old to the new platform
• Environment: IBM Mainframe, DB2, CICS, MQ, Red Hat Linux, Oracle, Kubernetes, Kafka, Helm, GitLab, Jenkins

• Identification of requirements (legal, organizational, and technical)
• Design of solution architectures
• Evaluation of concepts and technologies
• Preparation of decision templates
• Architectural Decision Records (ADR)
• Coordination of implementation
• Review of implementations
• Documentation

• Architected and deployed a live B2B geocoding and demographic-data platform for Germany, combining address lookup with census-based population statistics through a web application and REST API.

• 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.

• Migration of backups and complete workloads to AWS and Azure, including setup and management of AKS & EKS clusters.
• Automation with Terraform & ArgoCD, CI/CD pipelines implemented with GitLab.
• System monitoring on OpenShift 4 (on-premise) with Grafana & Prometheus, use of CloudWatch and X-Ray for analysis and logging.
• Building and maintaining secure network infrastructures (VPCs, SGs, WAF, ACLs), integration of Azure Log Analytics.
• Close collaboration with infrastructure and development teams, maintenance of technical documentation with Confluence, ticket handling via Jira, and promoting cloud knowledge within the company.

• Third-side integration development (REST: Amazon, OpenAI, Etsy, Shopware, Prestashop, etc)

• Performance optimization (Refactoring, SQL analysis)

• LMS development and deployment (Moodle)

• Cloud deployment automation (Amazon, Azure, Gitlab CI/CD, Docker)

• Backend and Frontend development (Laravel, VueJs)

• Collaboration with partner-developers (national and international)

• Shirtigo GmbH

• GRELLARTIG Digital GmbH

• velpTEC edutainment GmbH