WebSocket Experts

• Designing the audit logging framework
• Implementing APIs for developers to integrate in their codebase
• Implementing ingestion pipeline, database query layer and UI for browsing the audit events
• Improving stability and reliability of the backend system

• Own full-stack development of an AI-native enterprise platform built on TypeScript, React, Vite, tRPC, Hono, and PostgreSQL, delivering AI-powered consulting workflows to B2B clients.
• Designed and shipped a multi-agent AI system using ReAct framework and Claude skills-style workflow patterns, including an intelligent PM assistant with rich system prompts, slash commands, tool integrations, and streaming chat UI.
• Architected an LLM evaluation framework: rubric-based LLM-as-judge, golden datasets, regression testing, and automated quality gating — ensuring consistent AI output quality at scale.
• Integrated LangFuse for end-to-end LLM tracing, conversation replays, and evaluation pipelines, enabling data-driven prompt optimisation that reduced token costs and response variance.
• Built with Drizzle ORM, pgvector, and knowledge graphs for structured data access, semantic search, and relationship-aware AI reasoning across the platform.
• Led TanStack React Query migration across the application — replacing manual state management with centralised caching and automatic refetching, reducing data-fetching boilerplate significantly.
• Practiced AI-native development throughout: Claude Code, Codex, Perplexity SDK, and LLM-assisted testing across the full development lifecycle. Deployed on Vercel + Azure ACA with Biome for linting/formatting.

• Further development and operation of a central backend service for providing vehicle inventory for international Mercedes-Benz online shops
• Further development of a reservation service for vehicles as part of the checkout process
• Design and implementation of a highly scalable end-to-end test architecture with a focus on maintainability, reusability, and a high number of automated test cases
• Development of a multi-layer test infrastructure with a strict separation of test logic and access layers
• Development of an initialization and caching architecture to significantly speed up local and CI/CD-based test runs
• Development of an AI-supported review architecture for automated evaluation and quality assurance of end-to-end tests
• Development of a dashboard for consolidated display of a vehicle context across multiple backend systems, including AI-generated summaries and compact case analyses
• Integration and further development of connections to various reservation systems via Apache Kafka and REST
• Design of new microservices and support with architecture decisions
• Risk analysis and design of microservice migrations
• Technologies: Java, Spring, Spring Boot, Gradle, Maven, Apache Kafka, REST, OpenAPI, Swagger, Github, Confluence, CI/CD, Microservices, AI, LLMs

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.

PLANT-MY-TREE®-per-order

The application enables Shopify merchants to automatically place tree-planting orders for every incoming order. By integrating ecological contributions directly into the purchase process, the manual effort for tracking and billing reforestation initiatives is eliminated. The system increases transparency for end customers through real-time visualizations of the ecological impact directly in the storefront. The architecture is based on a modular monolith with Spring Boot in the backend and an integrated React app inside the Shopify admin area. The solution uses webhooks to capture order data in an event-driven way and integrates the weclapp ERP system for automated monthly invoicing. An app proxy mechanism provides dynamic statistics such as CO2 compensation and planted trees without any performance loss for the merchant shop.

Tasks:

• Design of the modular software architecture based on Spring Modulith to ensure high maintainability
• Development of the event-driven business logic for evaluating Shopify orders via webhooks
• Implementation of automated invoicing by connecting the weclapp REST API
• Building the frontend using React Router and Shopify App Bridge for native integration
• Design of the database model and implementation of the persistence layer with JPA/Hibernate and Prisma
• Integration of internationalization processes for global use in the frontend and email communication
• Automation of deployment processes using Docker and GitLab CI/CD

Project skills: Java 25, Spring Boot, Spring Security, Spring Modulith, Hibernate, JPA, REST API, PostgreSQL, Maven, Liquibase, React, TypeScript, React Router, Vite, Node.js, Prisma, Zod, Docker, Docker Compose, GitLab CI/CD, Shopify CLI, Shopify App Bridge, Polaris, weclapp, i18next, Lombok, Vitest

• Expert-supervised AI systems for scientific reasoning, model evaluation, and research workflows.
• Built the IAS Problem Solver, an orchestrated system for difficult mathematical reasoning; it achieved 84% in one submitted answer set on the Leipzig mathematics benchmark.
• Built a resumable state-machine pipeline for research-grade mathematics benchmark generation: source selection, LLM-agent-based phenomenon discovery, task synthesis, gold-answer and certificate generation and validation, probing, repair, human feedback, and quality gates, targeting tasks that are difficult, natural, verifiable, and cost-effective.
• Current work extends this into budget-aware AI research workflows for real scientific problems with expert review.

Tech stack: Python, OpenAI/OpenRouter-compatible APIs, embeddings, RAG, SQLite.

• Porsche ID is a unified digital identity platform providing secure authentication and seamless access across Porsche’s online services, mobile apps, and connected vehicle features
• Designed and implemented new authentication and authorization functionalities for both users and systems
• Ensured high availability, security, and performance to deliver a flawless digital experience for Porsche customers
• Technologies: Auth0, Angular, Tailwind, AWS, Terraform, Github
• Methodologies: Scrum and SAFe

• Built a complete real-time multiplayer platform with game engine, lobby system, game tables, spectator mode, and persistent game history.
• Implemented product-relevant multiplayer workflows with WebSocket communication, live synchronization, voice chat, mobile app features, and push notifications.
• Developed a scalable full-stack architecture with authentication, PostgreSQL persistence, premium/billing integration, and extensive test coverage.

Built charts for historical data, alarms, and downtime, plus enhanced interactive tables to efficiently track and compare oil-well performance. Eliminated 80% of high/medium security risks (Checkmarx) for the app. Optimized charting libraries, cutting usage from to 300–400MB for large data sets.

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

• Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
• Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.

Overall architecture and technical implementation of a Wix-based subscription frontend with Stripe payments and connection to Axxessio's SaaS backend. Implemented Stripe Checkout, subscriptions, webhooks, and transaction logging end to end. Customer data and contract information transferred automatically via a JWT-protected REST API. Designed and documented proxy and security architecture for IP whitelisting, HMAC, and operations, and aligned it with the backend team.

Stack: Wix Studio, Wix Velo, JavaScript, Stripe, Webhooks, JWT, HMAC, REST API, Hetzner, Cloudflare

• Working on the next iteration of tonbo to make it the most flexible in-process analytical database in the market that scales and is operated with strong availability

• Introduced object scope cache to the remote storage layer to avoid I/O churn

• Working on refactoring WAL to support remote storage

• Taking care of the health of the systems as well as designing the operational story and bringing them to production

• Technologies: LSM, WAL, Arrow, Parquet, Rust

• IT training in theory and practice for IT specialists in application development and system integration