Amazon Cognito Experts in Germany

• 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

Designed and developed an Azure-based AI and data platform transforming distributed project documents into searchable, structured knowledge for an enterprise AI assistant. Combined incremental document processing, hybrid keyword/vector retrieval, knowledge graph extraction, and conversational AI for Microsoft Teams and Microsoft 365 Copilot. Implemented Python document-processing pipelines for PDF, Word, Outlook and text files; Azure Cosmos DB lifecycle management; Azure AI Search; Azure AI Foundry and Azure OpenAI; identity-aware retrieval with Microsoft Entra ID; project authorization; a TypeScript Microsoft Agents SDK agent; Pulumi infrastructure; resilient scheduling, retry and diagnostic tooling. Technology stack: Python, TypeScript, FastAPI, Pydantic, Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Cosmos DB, Blob/Table Storage, Container Apps/Jobs, Service Bus, Key Vault, Entra ID, Docker, Pulumi, pytest, Microsoft Teams and Microsoft 365 Copilot.

• 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

• Responsible for the end-to-end application and integration architecture for the S-Bahn Hamburg maintenance digitalisation program. A highlight is the introduction of robots and permanently installed camera gates to automate vehicle inspections, allowing AI image algorithms to assess the condition of trains during operation.
• Deutsche Bahn has one of the largest SAP PM implementations in the world, which is a central component of this digitalisation.

Design and implementation of a compact ERP, CRM, accounting, and production-planning platform for a German food manufacturer. The system replaces Rechnung11, self-built Excel sheets, and manual processes for fewer than 10 internal users.

• Designed and implemented the full platform architecture as sole architect and developer.
• Built modules for customer management, B2B order handling, invoicing, production planning, and accounting support.
• Implemented DATEV export, ZUGFeRD/XRechnung e-invoicing, FinTS bank statement synchronization, and GoBD audit trail concepts.
• Used AI-supported workflows for prototyping, test support, and implementation acceleration while retaining full architecture, review, testing strategy, and technical ownership.

Technology: Java 23, Spring Boot 3, Spring Data JPA, Spring Security, Vue 3, TypeScript, PostgreSQL, Flyway, REST, OpenAPI, JWT, TOTP, RBAC, DATEV, FinTS, ZUGFeRD, XRechnung, GoBD, JUnit, Mockito, Testcontainers, Playwright, Docker, GitLab CI/CD

Conversational AI assistant for cloud infrastructure and security queries

• Designed FastAPI backend with multi-turn conversation handler, token budgeting, and context window management.
• Integrated Amazon Bedrock (Claude 3 Sonnet/Haiku); built RAG pipeline with MongoDB chat history and semantic search.
• Implemented Factory Pattern for modular LLM provider switching; reduced model onboarding effort by 60%.
• Reduced LLM inference cost by 35% through model tiering (Haiku vs Sonnet) and prompt/entity consolidation.

Tech: Python, FastAPI, Amazon Bedrock, MongoDB, Streamlit, Pydantic.

• Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
• Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
• Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
• Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
• Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
• Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
• Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
• Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
• Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
• Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
• Integration of RESTHeart to create a REST API for MongoDB.
• Build an Angular frontend to simplify data queries and master data maintenance.
• Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
• Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).

• Developing Kotlin/Spring Boot microservices deployed on Kubernetes and AWS Lambda
• Implementing monitoring solutions
• Backend development for Traigo platform (booking/analysis for freight wagons)
• Determining wagon stays in geofences
• Routing of position data
• Forwarding position data and geofence events to clients using ITSS
• Developing and deploying services in both Kubernetes and AWS Lambda environments
• Tech stack: Kotlin, Spring Boot, Kubernetes, AWS Lambda, PostgreSQL, DynamoDB, Protocol Buffers

• Extension and maintenance of the Doktree tax advisory document management tool
• Alfresco and Angular development
• Linux system maintenance

• Consulted on IT security and process optimization, focusing on NIS2 and risk requirements
• Troubleshot and optimized plant core networks using STP, certified hardware, and open-source components such as OPNsense
• Redesigned network segmentation for VLAN rollout in a hybrid multisite multicloud setup using Tailscale VPN
• Facilitated cross-departmental discussions to align technical and social requirements
• Optimized monitoring with Grafana, Telegraf, and SNMP configurations
• Prototyped network setup for a new plant, including VLAN separation with Tailscale VPN
• Automated various scenarios using Python and Bash scripting

• Worked on ideation phase through deployment; managed the team and implemented the core architecture
• Developed Firsty Travel eSim: native eSIM installation with a single click; seamless user authentication; real-time data synchronization; intuitive user interface design; advanced security protocols; integration with third-party services; high performance and scalability
• Developed WIO Business banking app: spend, save, invest, and control entire transaction process
• Technologies: Flutter, iOS, Android Studio

• Architected ETL services for event-driven data exchange between enterprise systems on a Kafka streaming backbone.
• Optimized CI/CD pipelines for Azure AKS deployments and improved OpenSearch monitoring and alerting for proactive incident detection.

Tech: Java / Kotlin, Quarkus, Kafka / Avro, Azure / AKS, Azure Storage Container, ArgoCD, GitLab CI, OpenSearch, Terraform

• Independently designed, developed, published, and maintained mobile games for iOS and Android.
• Implemented application architecture, gameplay systems, UI, monetization, analytics, and platform integrations.
• Managed the complete release lifecycle, including testing, store publication, production monitoring, and iterative improvements based on analytics.

• Test concept creation
• Creation of test processes
• Coordination of TC development: stress tests, functional tests, performance tests, high data rate tests, integration tests, etc.
• HW testing: FPGA, RF
• Test automation and regression tests
• Ensuring 24/7 operation of the test system
• Analysis & reporting
• Regular coordination of the test team, meetings with other stakeholders
• Communication and coordination with stakeholders and the project manager