GitHub Experts in Hamburg

• Owning RAG, LLM-System, ML-ops-Pipelines for various startups in Insurance, Banking, Energy (KRITIS)

Cloud Journey Kickoff on STACKIT

• Helped the client kickstart their cloud journey on sovereign EU STACKIT platform.
• Bootstrapped IAC & GitOps architecture with Opentofu and ArgoCD.
• Setup platform fundamentals for a fresh, holistic cloud experience: Kubernetes, external secrets, certificate management, gateway API, DNS & routing, observability basics.

• Lecturer for applied AI in the “AI Implementation Architect” and “AI Business Innovator” courses
• Conducting remote training to qualify participants as "AI Implementation Architect" and "AI Business Innovator"
• Building n8n-based automations for the Digital Institut des Mittelstands

• Building a data integration platform for high, medium, and low voltage assets for contextual analysis of time series with master data from the SCADA control system (IEC 60870 104), INIS, and SAP.
• Responsibility for the architecture and implementation of the solution, as well as sparring partner for the Product Owner.
• Use of Kotlin, Spring Boot, Maven, TimescaleDB, PostgreSQL, liquibase, Elements IoT, Docker, Kubernetes, Grafana, Python, jupyter, and various API gateways.

• Assumed responsibility for backend architecture and technical strategy, planning and leading the platform's evolution in close collaboration with the CTO
• Simultaneously drove the development of new features for the housing and tenant management platform, balancing high-level architectural design with hands-on implementation
• Utilized AI-assisted workflows (with tools such as Claude Code, Codex, Cursor) and worked on AI-based features (with tools such as N8N, Mastra, ElevenLabs)

Technologies: Node.js, TypeScript, React.js, Next.js, PostgreSQL, Google Cloud, Docker, Kubernetes

Co-founded a software agency building custom web and cross-platform products. I owned the technical decisions across the whole portfolio and led 12 people, while carrying delivery planning, process and client relationships for 11 clients across 3 industries.

• Technical leadership: owned the technical decisions for the codebase across every project — stack, architecture, code conventions and the tooling the team worked with — and led the developers on how work got built through code reviews, pair programming and mentoring across a team ranging from junior to senior, keeping the codebase coherent as the portfolio and the team grew

• Delivery planning against the financial plan: built the company's financial plan and derived from it the billable hours each developer had to reach per month and the hours each project could absorb to stay within budget; planned capacity and scope against those figures and negotiated budgets and delivery dates directly with clients

• Client ownership: technical contact across the portfolio — requirements gathering and prioritisation, scoping and estimates, timeline communication, budget negotiation, and consistent transparency throughout delivery

• Team and people: owned the hiring and interview process end to end and took responsibility for offboarding where it was needed; designed an onboarding that got new developers productive within 1–2 days; cleared blockers daily and kept a close eye on where effort was creating value and where it was not

• Process ownership: consolidated a micro-service landscape spread over 15+ repositories into a single monorepo, cutting backend development time by ~40% and simplifying releases for 6 engineers; set up deployment pipelines with GitHub Actions and GitLab CI; ran retrospectives and turned the feedback into concrete changes; introduced AI agents into day-to-day development

• Delivered short-staffed: when the team shrank from 8 developers to 2, restructured scope, introduced AI-assisted development to hold the schedule and took on Go backend work alongside my own frontend scope

• Architecture and code: defined the architecture for every project in the portfolio — the structure the rest of the team built within — and wrote roughly 90% of the frontend code myself, from SSR applications with Next.js and Remix to cross-platform apps with Capacitor

• From zero to production: took a practice management platform — administration, inventory, integrated online shop, chat messenger — from an empty repository to production. Live in 7 markets with at least 7 more coming up, serving tens of thousands of users

• Delivery under pressure: built and shipped a replacement online shop for a Fortune 250 client in 4 days, restoring order intake while their global shops had been offline for several weeks

• Design system: built a cross-project design system used across 7 products, so new projects and features started from a shared, consistent base

• Cross-platform and real-time: built iOS and Android apps with Capacitor for a client live event with 1,000+ participants — web sockets and push notifications for real-time content, Stripe payments supporting PayPal, Apple Pay, Google Pay and cards

Key technologies: React, TypeScript, Next.js, Remix, GraphQL, ConnectRPC, Redux, Zustand, Go, Node.js, Turborepo, Nx, Capacitor, Ionic, WebSockets, Stripe, PostgreSQL, Playwright, Cypress, Vitest, Storybook, GitHub Actions, GitLab CI, Claude Code, Cursor, GitHub Copilot

• Onboarded and conducted comprehensive documentation and system analysis to assess the existing data infrastructure, facilitating rapid integration and collaboration across functional data teams (modelling, processing, reporting).
• Collaboratively defined the architecture and project structure for a central data pipeline repository, including hierarchical standards, knowledge management strategies, and role-specific responsibilities, enhancing maintainability and onboarding speed.
• Evaluated and validated open-source data routing tools (Airbyte, Apache NiFi, Dragster) for ingest and sync requirements in retail analytics, including local benchmarking and error-state testing.
• Led the design and deployment of Airbyte in Kubernetes, creating customized Helm charts, securing secrets handling, and configuring Ingress with TLS and internal DNS routing, ensuring full API and UI accessibility.
• Troubleshot and resolved Ingress controller issues, iterating through multiple stages of debugging and testing, and documented setup and replication steps for scalable reuse.
• Mapped data models to ARTS standard, supporting schema alignment for ERP and reporting use cases, and coordinated review loops to align future data processing logic.
• Drafted strategic 1-pagers comparing MinIO, Pub/Sub, and routing architectures, providing technical guidance for architectural decisions and investment planning.
• Enabled secure access and authentication mechanisms, including initial evaluation for SAML integration, cluster-level configuration reviews, and service annotation improvements.

• Lead architect for an enterprise loan digitisation programme, coordinating 12 engineers across five workstreams and serving as final technical authority on system design.
• Cut critical application response times by 68% (display 17.3s → 5.6s; modification 11.8s → 5.0s) through targeted caching, OData query optimisation and lazy-loading refactoring; further optimisation in progress.
• Own production error triage, prioritisation and resolution across a multi-application portfolio supporting live lending operations.
• Design and implement SAP Fiori applications on SAP UI5, TypeScript and RAP, owning delivery from architecture and code through rollout and production support.
• Established C4 architecture documentation and decision records for the full programme, enabling faster onboarding and consistent cross-workstream design governance.
• Co-managed S/4HANA release cycle alongside primary responsibilities, coordinating directly with SAP support to resolve critical system issues across the portfolio.

• work in the Developer-Experience team to improve developer experience and tooling for all teams of the RTL+ streaming platform
• development of reusable GitLab CI/CD components to standardize processes and automatically enforce code quality and security gates
• infrastructure automation with Pulumi
• operation and monitoring of GitLab Runners in AWS with Kubernetes
• integration and automation of Renovate in GitLab pipelines for continuous dependency updates
• extension of Backstage as the central developer platform to optimize internal workflows and self-service capabilities
• development of various tools and automations in TypeScript, Go, and Python

traigo is VTG's digital rail logistics and fleet management platform. It processes large volumes of telemetry, mileage, geofence, sensor and wagon-movement events in near real time and provides operational services for rail logistics customers across Europe.

As part of Team Customer Selfcare, I worked on the design, implementation, optimisation and operation of large-scale backend services and event-driven processing pipelines — covering both feature development and operational ownership of business-critical production systems. I also regularly acted as first responder for production incidents, data inconsistencies and performance investigations across multiple distributed services.

• Design and implementation of event-driven backend services.
• Migration and replacement of legacy processing pipelines.
• Development of replay / rebuild mechanisms for large event datasets.
• High-throughput asynchronous event processing on SNS / SQS.
• Database and query optimisation for PostgreSQL and DynamoDB.
• Design of scalable read / write models and aggregation pipelines.
• Production troubleshooting and operational support.
• Performance tuning and infrastructure scaling.
• Design and stabilisation of integration and system tests.
• Technical concepts, architecture documentation, and cross-team collaboration.
• Support the further development of existing GitLab CI/CD pipelines

Geofence & Wagon Stay Processing

• Algorithm to detect vehicles within geofences (entry, exit, dwell time).
• Event sourcing with guaranteed chronological order within the affected time window.
• Refactored geofence event and wagon-stay processing logic for performance.
• Resolved race conditions and event-ordering problems in distributed services; server-side filtering, aggregation and optimised query pipelines.
• Repair and replay tooling for corrupted or inconsistent movement data.

Fleet Metadata & Mileage

• Modernised the service; migrated storage from DynamoDB to PostgreSQL to improve traceability and accelerate new features.
• Scalable mileage aggregation and replay mechanisms.
• Read / write models and optimised queries for high-volume mileage calculations.

Sensor & Telematics Integration

• Integrated telemetry and sensor processing pipelines.
• Snapshot and state-calculation logic for sensor systems.
• APIs and persistence models for wagon sensor data; data-quality improvements.
• Further development of a service using gRPC for intra-service communication.

Movement Segment Processing & Routing

• Migrated services to new movement-segment event streams.
• Built replay and rebuild tooling for segment correction.
• Optimised throughput and reliability for high-volume event processing.

Condition Monitoring & Wagon Analytics

• APIs and backend services for wagon condition monitoring.
• Brake-wear prediction processing and wagon analytics functionality.
• PostgreSQL views and optimised query models for operational dashboards.

Operational Reliability - First Responder

• Investigated production incidents and distributed-system failures; DLQ analysis, replay and operational recovery.
• Tuned database performance and AWS infrastructure under production load.
• Improved observability, monitoring and operational tooling.
• Supported rollout strategies, monitoring and post-deployment stabilisation.

• Industry: SaaS (Customer Success Management) – B2B

Comprehensive GEO implementation (Generative Engine Optimization) for a B2B CSM SaaS startup with a focus on AI Search Visibility and AI Citations in ChatGPT, Perplexity and Google AI Overviews – including a GEO workshop and a prioritized implementation roadmap.

• GEO Workshop & Roadmap: Conceptualized and delivered a GEO workshop (how LLMs work, AI Search Architecture, citation strategies); translated it into a prioritized implementation roadmap with impact/effort estimates
• Technical GEO Foundation: Robots.txt & llms.txt, Core Web Vitals & page speed, XML sitemaps for AI crawlers
• Schema & Structured Data: Gap analysis, implementation of Product/Service, FAQ, Article, Author and Organization schema, validation of coverage
• Content Architecture & GEO: Flat content architecture, topic clusters (pillar-and-spoke), 200–300 word chunks and answer-first content structure, E-E-A-T rollout through author pages
• Query Fan-Out & Prompt Anticipation: User prompt mapping, query fan-out, content gap analysis based on prompt coverage
• Citation & Backlink Strategy: AI citation analysis (news, Reddit, Wikipedia, listicles) and development of outreach and backlink strategies

Tools & technologies: Otterly.AI, PeecAI, Qforia (iPullRank), Schema Markup Validator, OpenAI Tokenizer, Prompt Coverage Monitor, ChatGPT, Perplexity AI, Semrush, Ahrefs, Framer CMS

• Developing a professional appointment planner for organizations with specific, detailed requirements
• Evaluating various existing software solutions
• Creating a list of technical requirements
• Implementing these requirements
• Technologies under consideration: WebDAV, CalDAV, Rust, Baikal, OAuth, Keycloak

• Environment: AWS, Ruby on Rails, GraphQL, React Native
• Penetration test for Backend, Android-App and iOS-App

• Successfully completed a 3.5 month data science course, earning the ‘Certified Data Scientist’ title from XDi, Germany (AZAV certified).
• Covered supervised and unsupervised machine learning algorithms.
• Covered natural language processing using Python.