Microservices Experts in Dortmund

Development and evolutionary further development of a highly available, cloud-native microservice and integration architecture for dealer and retail processes in the Porsche Car Configurator.

Responsibilities

• Development of Java-/Kotlin-based backend, API, and integration components (Spring Boot)
• Integration of internal and external systems via REST/OpenAPI, GraphQL, Apache Kafka, and AWS SQS (synchronous and asynchronous)
• Implementation of stable, high-performance communication and data flows in a cloud-native platform architecture
• Processing of structured data formats (JSON, Protobuf, GraphQL schemas) based on existing API patterns
• Performance optimization of distributed microservices with reduced response times and higher operational stability
• Technical tests (unit, integration, and API tests) as well as error analysis in production-like environments
• AWS Infrastructure as Code with Terraform and AWS CDK
• CI/CD automation (build, test, and deployment pipelines) with GitHub Actions
• AI-supported feature implementation (GitHub Copilot Agent)

Label: Kotlin, Java 25, Spring Boot 4, Protobuf, TypeScript, AWS, Terraform, CDK, Apache Kafka, AWS SQS, REST/OpenAPI, GraphQL, JSON, PostgreSQL, Docker, GitHub Actions, Maven, Gradle, JUnit, Mockito, Testcontainers

Manufacturing intelligence platform with enterprise workflows, RAG, real-time AI assistant features, and multi-repository backend architecture.

• Built and extended production AI/backend services with Django, DRF, FastAPI, GraphQL, Celery, PostgreSQL, MySQL, Redis, and WebSockets across a modular multi-repository platform.
• Contributed to ARIS V2, a real-time manufacturing AI assistant using LangChain, LangGraph, MCP tool orchestration, planning/execution flows, OpenAI, AWS Bedrock, Qdrant, and Elasticsearch/OpenSearch-backed retrieval.
• Supported rollout expansion from ARIS V1 in 4 of 17 client production plants to ARIS V2 currently active in 13 of 17 plants, increasing real-world deployment coverage to more than 50% of the client footprint.
• Worked on document-grounded RAG functionality including ingestion, OCR, chunking, embeddings, indexing, retrieval, reranking, and grounded answer generation for industrial workflows.

Stack: Python, Django, DRF, FastAPI, LangChain, LangGraph, GraphQL, Celery, WebSockets, OpenAI, AWS Bedrock, Qdrant, Elasticsearch/OpenSearch, PostgreSQL, MySQL, Redis, Docker.

• Complete greenfield rebuild across the whole stack — built AI-native: backend in Go and NestJS, PostgreSQL (CNPG) on K3s with GitOps/Terraform; frontend on Angular 22, zoneless.
• Orchestrated coding agents (e.g. Claude Code, Cursor) across the entire lifecycle — architecture, implementation, testing, reviews, documentation — driven by Specification-Driven Development (SDD).
• “Bruno” — LLM commentator persona backed by RAG and MCP for a personality that stays consistent across all generations (match previews, post-match reports, his own virtual bets).

Angular 22 (zoneless, without Zone.js), Claude Code, Claude Code Skills, CNPG, Cursor, Design Tokens (Spec for Code), Docker, Gherkin, Git, GitLab, GitOps, Go, Google Gemini, Grafana, Hetzner Cloud, K3s, Keycloak, Kubernetes, Lighthouse, LLM Integration, Model Context Protocol (MCP), NestJS, Node.js, NPM, Playwright, PostgreSQL, Prometheus, RAG, REST, Specification-Driven Development (SDD), Structured Outputs, Terraform, TypeScript, Vitest

Building an observability and alerting solution for Business Central Job Queue monitoring

• Built a central monitoring solution to track the Business Central Job Queue in a multi-organization environment in Azure DevOps
• Integrated Azure Application Insights and Log Analytics for structured collection and analysis of job runtimes and error events
• Developed KQL queries for targeted analysis of failed jobs and detection of error patterns
• Connected Grafana and Power BI to visualize operational metrics and job status in real time
• Implemented an automated alerting workflow with Power Automate – when a job fails, a notification email is sent immediately
• Ensured transparency about the state of productive background processes during live operations

Result: Full transparency over failed Business Central jobs · Clear reduction in response time through automated email alerting · Stable foundation for proactive operation of productive background processes

Technologies: Azure DevOps | Application Insights | Log Analytics | KQL | Grafana | Power Automate | Power BI | Business Central | Azure Monitor

• Development of the unified CARIAD E3 2.0 software platform for future mobility
• Stakeholder management
• Synchronization and alignment with solutions (UX, security, data product & mobility services, architecture, software product, integration)
• Workshop and migration management
• Conducting risk matrix analyses
• Tool use: Jira, Confluence, Codebeamer

• Various small consultations, e.g. concepts and arcitectures.
• Updating my Matlab, Linux, IPv6, Cyber-Security, C++ (up to 23) and Python skills.