PostgreSQL Experts in Dortmund

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.

• Delivered MVP-focused full-stack architecture for a health-sector client: Vite/React frontend, backend services on Google Cloud Run, and Supabase for database plus IAM/authentication.
• Supported product requirements engineering and prioritized cost-aware workload placement, implementing browser-side/edge computation where feasible before moving logic to backend services.

• 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

• Technical design, prioritization, and hands-on implementation of AI automation, conversational AI, voice AI, and private AI solutions.
• Translation of business requirements into system architecture, conversation/workflow logic, APIs, data flows, and production-ready AI workflows.
• Development of backend and integration components with Python/FastAPI, PostgreSQL/pgvector, Redis, REST APIs, webhooks, and background jobs.
• Design and implementation of RAG architectures with local/private LLMs, embeddings, document processing, semantic search, and controlled access to company knowledge.
• Prompt engineering for LLM and voice/conversational AI applications; iterative optimization based on real processes, system responses, and quality requirements.
• Practical work with ElevenLabs and its APIs in a voice AI project, as well as technical evaluation and integration of voice AI components.
• Deployment and operation of Docker-based systems on Linux with Nginx, CI/CD, monitoring/logging, backup/restore, and reproducible deployment processes.

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

• Built a central monitoring solution to monitor the Business Central Job Queue in a multi-organization environment in Azure DevOps
• Integrated Azure Application Insights and Log Analytics for the 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 statuses in real time
• Implemented an automated alerting workflow with Power Automate – an email notification is triggered immediately when a job fails
• Ensured transparency into the status of productive background processes during ongoing operations

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

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

• DTO class generator: In-house development of a tool for the automatic generation of classes, functions, and methods for use in .NET Core projects based on SAP Business One Service Layer metadata
• E-invoice import add-on: Development of a SAP Business One add-on / coresuite module for the automated import of ZUGFeRD e-invoices as incoming invoices – with configurable mapping to flexibly control the import logic across four mapping types (DIRECT, SQL, FIXED, EXPR). The add-on is available as a licensed product for SAP Business One customers.

Stack: SAP Business One, SAP Business One Service Layer, coresuite Country Package, C#

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

• Technical lead of a team developing agentic chatbot solutions (React, TypeScript, Python, FastAPI)
• Architecture design for multi-LLM dialog systems - focus on maintainability, UX, and autonomous execution
• Stakeholder alignment, CI/CD processes, and AI integration at enterprise level

• Development of software and system support for RPG development.
• Development, optimization and maintenance of programs in RPG (RPG II to ILE Free Format).
• Performing integration tasks, data management as well as applying and managing system updates.
• User support and training to ensure smooth system operation.

• Led the 12-week training program to become an AI and automation specialist
• Created training materials & video courses on "AI Fundamentals", "Working with ChatGPT", "Prompt Engineering", "AI Agents with N8N", "Automations with Make.com" & AI-generated marketing content (images, videos, blog posts & social media posts)
• Conducted workshops on the above topics
• Tools: Loom, N8N, Make.com, ChatGPT, Midjourney, Gamma.app, Canva, Kling AI, Magnific AI
• Result: Participants learn the technical and business know-how to successfully build a business as AI and automation specialists

• Initial assessment of requirements based on a business value prioritization framework
• Identification of issues as well as requirement gathering and evaluation using UML, BPMN, and design thinking methods for iterative requirements analysis through interviews and workshops
• Use of user story mapping in Miro to visualize and align functional requirements (e.g. correct transmission of all application data and attachments to the specialist system) as well as non-functional requirements (e.g. complete and verifiable deletion of an applicant's data) with stakeholders
• Proactive stakeholder management of internal and external stakeholders from public authorities, business units, organizations, and companies
• Preparation of status reports to communicate project progress and upcoming tasks transparently
• Responsibility for a REST-based integration solution (middleware) for secure data exchange between core systems and external specialist applications; ensuring stability and performance in day-to-day operations
• Support for Product Owners in prioritizing backlog items and in product discovery
• Communication of planning to internal and external stakeholders as well as interim assumption of Product Owner tasks and responsibilities during a staff change

• Further development and release support for a white-label ePA component for health insurance companies
• Technologies: Android (Kotlin), Kotlin Multiplatform, Coroutines, Jetpack Compose, MVVM, StateFlow, Gradle, ProGuard

• Designed and implemented the system architecture for scalable document workflows, improving stability and performance.
• Optimized the login flow with TOTP-based MFA, reducing complexity and login time by 35%.
• Built secure backend APIs for document upload, signing, and management.
• Developed encrypted file handling with AWS S3 pre-signed URLs, ensuring GDPR-compliant data protection.
• Implemented JWT-based role authentication, strengthening access control and overall platform security and reducing code and database complexity.
• Optimized database queries and caching using ORM, reducing API response time by 40%.
• Integrated real-time webhook updates, enhancing workflow transparency and user experience.