OpenID Connect Expert

• Developed a browser-based platform for Kubernetes no-code deployment and cluster management
• Developed a CLI in TypeScript to deploy resources in the cluster without leaving the browser UI.
• Implemented DevSecOps pipelines: image scanning, SBOM, policy enforcement, supply-chain security, and used Kyverno. Implemented IAM integration for the command-line utility tool.
• Designed role and permission models for Keycloak, OAuth/OIDC, and social login flows.
• Used LLMs to convert user intent into diagrams.
• Worked on integration with multiple sovereign clouds like StackIT, Hetzner, CIVO, UpCloud, plus public clouds like AWS, GCP, and Azure
• The technology stack includes Java, Spring Boot, Kubernetes, OpenAI, Kubernetes multi-tenancy using vCluster, Karpenter, RBAC for CLI, Helm, React

Built an international e-commerce platform for a multi-vendor marketplace for digital assets from scratch. Designed and operated cloud native architectures at enterprise scale.

• Designed and operated a highly scalable microservice and serverless architecture
• Built the complete cloud infrastructure with Terraform + AWS CDK in AWS
• Provisioned ECS/EKS clusters (Fargate), Application Load Balancers (reverse proxy), and Lambda functions
• Observability & tracing with CloudWatch, DataDog, Prometheus, and Grafana
• End-to-end setup with DataDog (formerly AWS CloudWatch), Prometheus, and custom Grafana dashboards
• Integration of advanced metrics (including ORM mapper) and distributed tracing with Jaeger
• Robust backup and disaster recovery strategies
• RDS Postgres backups and hourly snapshots
• Read-only, asynchronously synchronized replicas with automated master failover in emergencies
• Minute-level rollback capability through versioned Docker images on ECS and Git-based CI/CD pipelines
• Created CI/CD pipelines with GitHub Actions for automated multi-stage deployments (Dev, Testing, Prod)
• Integrated Stripe for international payment processing
• Built a marketplace payment system with multiple parties and payout routines
• Used Algolia for high-performance real-time search of digital assets on the platform
• Federation of services with GraphQL and Hasura
• Later migration to GraphQL Mesh
• Test Driven Development (TDD) - unit, integration, and E2E testing with Jest, Vitest, and Playwright
• Used Next.js / React for modern frontend applications in the nx monorepo
• Enterprise security architecture & access control
• Integration of JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA protection, and secret vaults
• Authorization concepts with RBAC, ABAC, and native Postgres Row-Level Security (RLS)
• Built internal microfrontends with Retool for fast prototyping and operational business processes

Technologies: ABAC, AWS CDK, AWS CloudWatch, AWS ECS, AWS EKS, AWS Fargate, AWS RDS, AWS S3, Algolia, Auth0, DataDog, Docker, GitHub Actions, Grafana, GraphQL, GraphQL Mesh, Hasura, JWT, Jaeger, Java, JavaScript, Jest, Kotlin, Kubernetes, Monorepo, Next.js, OIDC, Playwright, Postgres, Postgres RLS, Prometheus, RBAC, Redis, Retool, Serverless, Stripe, Terraform, TypeScript, Vitest

• Planned and developed a CPU monitoring application for monitoring system performance and resource utilization.
• Designed and implemented a Spring Boot backend providing a REST API for processing and exposing monitoring data.
• Developed the React frontend for presenting monitoring information in a clear and user-friendly interface.
• Integrated PostgreSQL for persistent storage and management of application data.
• Containerized the application and its services using Docker Compose.
• Automated infrastructure provisioning and deployment using Terraform on AWS.
• Structured the application as a modern, maintainable system using REST-based communication between frontend and backend.
• Designed and developed a secure, scalable CPU monitoring architecture (cpu-watcher) with a dedicated collector application that streams monitoring data to the backend, reducing direct exposure of system resources.
• Designed a secure cloud infrastructure with the database isolated within a private network and OIDC-based authentication.
• Implemented Infrastructure as Code with Terraform and integrated version-controlled CI/CD pipelines to automate testing, infrastructure changes, and application deployments.
• Designed and implemented the frontend delivery architecture using AWS CloudFront.

Stack: Spring Boot · React · PostgreSQL · REST API · Docker Compose · Terraform · AWS

• Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
• GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
• AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner

Product:

• Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
• Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
• Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
• Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
• Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.

Agent Orchestration & RAG Systems

• Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
• Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.

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

• Ride-sharing and bus platform, live and fully functional. Backend with Spring Boot 4.1 on Java 21, PostgreSQL with Flyway, and Testcontainers integration tests. Hosted in my own AWS account (ECS Fargate, ALB, ECR, IAM Least-Privilege) with CI/CD via GitHub Actions and OIDC federation without static credentials. Development fully AI-supported with Claude Code, including custom skills and project-specific memory. Spring Boot · Java 21 · PostgreSQL · Flyway · Docker · AWS ECS/ALB/ECR · CI/CD · GitHub Actions · Claude Code

• Client: Prime Force Group GmbH

Technologies used: Java 25, Spring Boot 4, MapStruct, JSpecify, PostgreSQL, Redis, Liquibase, REST/OpenAPI, Apache Kafka, Apache Solr, OpenID Connect via IronGate/Keycloak, SAP Customer Data Cloud, JUnit, Testcontainers, Karate, Playwright, GitLab monorepo with CI/CD, Jenkins, JFrog Artifactory, FluxCD, Docker, Kubernetes on Azure, OpenTelemetry, arc42, Jira, Confluence

The Team Management Center is the new central platform of the DFB for planning, managing, and carrying out team activities for the national teams - from squad selection and training camps to communication with players, clubs, and legal guardians. The platform is designed for multi-tenancy for the DFB and regional associations; player, club, and master data are intentionally not copied, but connected at runtime via the DFBnet APIs.

I have been involved in the project continuously since the architecture and concept phase (Sprint 0) and work in a distributed Scrum team in two-week sprints. In addition to implementation, my focus is on architecture alignment, connecting the DFBnet interfaces, as well as code reviews and test automation as quality assurance in the team.

Focus areas:

• Development and implementation of the multi-tenancy concept (tenant model for the DFB and regional associations), including data model, access layer, and Liquibase migrations.
• Design of the person service and the search concept based on Apache Solr.
• Integration of the DFBnet APIs (player, person, and club search, club data), including authentication and synchronous master data synchronization.
• Hardening the integration through resilience patterns: separate read timeouts for each search path, correction of circuit breaker counting, limiting parallel requests, and a club cache to reduce load on the external system.
• Development of self-service endpoints for players (own activities, activity details, games), including an access concept for participants, as well as person documents and file uploads.
• Standardization of API design: OpenAPI annotations, nullability model via a custom ModelConverter, JSpecify migration of the DTOs, and documented API guidelines.
• Build and maintenance of Karate-based API and integration tests, integration tests with Testcontainers, test guidelines, and bug triage from the integration and reference environments.
• Code reviews via merge requests, architecture documentation according to arc42, and architecture decisions (ADRs) in Confluence.
• Automated deployment to the integration and reference environments, analysis of login and OIDC issues in combination with IronGate.

Status: ongoing - as of 08/2026 in Sprint 17, around 940 person hours worked; testable delivery to the integration environment every two weeks.

• 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

IT consulting, analysis, architecture design, new and further development, code review, test automation, continuous integration, continuous delivery in backend and frontend areas for Automotive Project Instavalo.

Frontend:

• Implementation of UI components according to specifications, especially style guides and responsive design eith React and Typescript
• Component testing
• Code documentation
• CI/CD with Gitlab Pipeline

Backend / IoT:

• Analysis and architectural design with AWS Greengrass IoT on Edge Devices
• Setting up Microservices containers with Docker Compose on Edge device with AWS Greengrass and AWS IoT IAM, Token Exchange Service, Ansible
• CI/CD with Gitlab Pipeline, Terraform, AWS ECR
• Logging with Fluentbit Lua Language for AWS Cloudwatch
• Python Lambda for AWS Greengrass Recipe deployment on Edge Devices
• Implementation of test-driven development with JUnit, Mockito, and code Coverage
• Jacoco
• Definition of REST interfaces with OpenAPI / Swagger
• Development and enhancement of software based on Java Quarkus, Typescript NestJs NodeJs and Python
• Authentication and authorization in Aws IAM
• Development of REST and gRPC interfaces for the frontend and backend
• Implementation of Maven dependencies with DevSecOps OWASP
• Spring AI, Jetbrains AI Assistant, Junie, Github Copilot, Claude Code, Agents, Skills, Command, Hooks, Subagents

• Short description: Lead a group-wide project to establish standardized cloud governance for Microsoft Azure, including policies, security and compliance controls, automation, and cost and operations control while preserving the autonomy of decentralized business units within regulatory boundaries.

• Tasks and activities:

• Overall responsibility for the design, setup, and implementation of an enterprise-wide cloud governance structure (Azure), incl. target picture, roadmap, and operating model.

• Management of internal and external stakeholders (C-level, IT, Security, Compliance, Cloud Architecture, DevOps) incl. decision-making and escalation management.

• Planning and facilitation of workshops on cloud strategy, governance principles, and the design of areas such as Identity, Connectivity, and Platform Management.

• Definition, implementation, and rollout of cloud policies (Azure Policy / custom policies), security standards, and compliance requirements (including GDPR, ISO 27001, BSI C5).

• Building a cloud governance framework aligned with the Azure Cloud Adoption Framework (CAF), incl. landing zone and guardrail concepts.

• Introduction of automation solutions for governance, security, and cost control (policy/control automation, IaC, CI/CD-based control mechanisms).

• Implementation of cloud security and compliance monitoring mechanisms as well as continuous improvement processes.

• Establishment and operationalization of FinOps in an enterprise environment (central and decentralized FinOps teams), incl. cost management strategies, reporting, and guardrails.

• Integration of governance policies into DevOps processes (e.g. CI/CD principles for security and compliance checks, GitLab Runner concept in spokes, GitLab CI/CD for CAF landing zones).

• Implementation of access concepts incl. RBAC design and "break glass" mechanisms (emergency access) as well as certificate automation (ACME / step-ca).

• Achievements:

• Created a unified, auditable governance and control set for Azure (policies, standards, compliance mapping) and thus laid the foundation for scalable cloud usage in a regulated environment.

• Established repeatable automation for governance, security, and cost control (IaC + CI/CD), reducing manual effort and implementation risks.

• Improved operational and decision-making capabilities across central and decentralized units (clearer roles, responsibilities, escalation paths, balance between autonomy and group requirements).

• Significantly increased workload compliance for lift-and-shift migrations.

• Technologies used:

• Microsoft Azure Policy, custom policies.

• Terraform, OpenTofu, Terragrunt.

• step-ca (ACME).

• Entra ID.

• Azure Firewall.

• Azure networking, hub-and-spoke architecture.

• Azure vWAN (evaluation).

• Azure Front Door, Azure Application Gateway.

• Azure ExpressRoute.

• Azure Key Vault.

• NetBox.

• GitLab (on-premises).

• Infrastructure, concepts used:

• Cloud shared responsibility model.

• Hub-and-spoke connectivity / central shared services (from a hub-spoke context).

• Central governance with decentralized delivery (business unit autonomy with guardrails).

• Methods used:

• Scrum.

• Stakeholder management (C-level to engineering).

• Cloud governance, Azure Cloud Adoption Framework (CAF).

• DevOps, CI/CD.

• Cost and FinOps approaches: tagging/chargeback models, budget/alert concepts, reserved instances/savings plans vs. on-demand scenarios, sensitivity analyses.

• RBAC, "break glass" concepts.

• ACME / certificate automation.

• GitLab Runner concept in spokes, GitLab CI/CD pipelines for CAF landing zones.

• Led migration to GCP using Terraform, GKE, and GitOps, improving deployment consistency and scalability
• Implemented Datadog observability stack via Terraform and datadog-operator
• Established automated end-to-end tests and on-call processes, improving incident response and service reliability
• Migrated from NGINX Ingress Controller to Kubernetes Gateway API (NGINX Gateway Fabric)
• Migrated stateful services (PostgreSQL and Redis) to GCP, improving scalability and operational reliability

• Error analysis and fixes including performance optimization of the in-house developed platform API
• Change and incident management in day-to-day operations
• Responsible for compliance with security and compliance requirements
• Vendor management for software development and maintenance
• Planning and execution of migration of legacy services to a cloud native platform

Role in the project: project staff, implementation team

Used skills: requirements analysis, IT service and application management, IT operations, error analysis and performance optimization, software maintenance and lifecycle management

Project environment: Cloud Native Platform (Kubernetes, Crossplane, AWS, ArgoCD, Grafana)

• Development and introduction of operations processes
• Preparation of complete documentation packages (including incident management and operations support) to meet compliance requirements
• Introduction of a workshop on IaC (Infrastructure as Code)
• Technical consulting for the project security concept (ISMS)
• Installation and operation of Kubernetes clusters on AWS, on-prem, and Azure
• Hybrid cloud architecture design (on-prem, Hetzner, AWS)
• Analysis and troubleshooting of incidents and system outages
• Network adjustments for firewall rules, gateways, OpenVPN settings, and IPsec tunnels (pfSense)
• Technical consulting on Bitbucket, Jenkins, and GitLab CI/CD pipelines
• Consulting on Ansible deployments and infrastructure automation
• Consulting on building a scalable system in the cloud (AWS / Azure)
• Technologies / Tools: Ansible, Terraform, AWS, Azure, VPN, pfSense, Jenkins, Bitbucket, Kubernetes, GitLab Runner, ISMS, Golang, Prometheus, Grafana, S3, Lambda, RDS, ECS, Cognito, OIDC, Harbor, MinIO, Postgres, Redis, Keycloak, Ceph, Proxmox, CloudFormation, PostgreSQL, Flux CD, Hetzner, IONOS, Sonatype Nexus Repository, Entra ID, Dex IdP, Pulumi