Electron Experts in Germany

Independent, part-time open-source engineering focused on build-time tooling for Next.js, React, MDX, and JavaScript/TypeScript compiler pipelines.

• Built next-slug-splitter to optimize content-driven Next.js applications. It analyzes MDX content at build time, resolves component usage, and generates route-specific handlers so pages avoid sharing the full catch-all component bundle.

• Created supporting plugins and utilities for scoped MDX transformations, nested component dependency resolution, compile-time refinement, safe ESTree evaluation, and object-graph diffing.

• Own architecture, API design, implementation, automated testing, npm publishing, documentation, demos, and performance benchmarking.

Building blocks:

• remark-scoped-mdx: Context-aware AST transformations with nested scope isolation, typed component registries, and prop inference.

• recma-component-resolver: Dependency-graph analysis and selective component forwarding across nested MDX includes.

• recma-static-refiner: Build-time prop extraction, schema validation, derivation, and pruning.

• estree-util-to-static-value and object-graph-delta: Safe static evaluation and deterministic, cycle-safe structural diffing.

Tech Stack:

• Frameworks: TypeScript · Next.js · React · MDX

• Compiler tooling: Unified · Remark · Recma · MDAST · ESTree · ts-morph · esbuild

• Competencies: Static analysis · AST traversal and transformation · dependency graphs · code generation · schema validation · route and bundle splitting

• Tooling: Vitest · tsup · npm · performance benchmarking

agentic-engineer.online is my publicly testable live demo and at the same time the platform where I show my work. Originally created as a recruitment trial task, I have since continued to run it as my own demo, learning, and product project — on a Hetzner VPS behind a Cloudflare tunnel, through a multi-stage AI-orchestrated deploy pipeline with snapshot rollback. If a deploy step breaks, the system falls back to the last clean snapshot, the script is adjusted, the test repeated — empirical, test-driven, without hand tuning.

• Technically behind it: Python and FastAPI, an OpenRouter model cascade, SQLite persistence, and Cloudflare edge tuning.
• I am the developer and the strictest customer of my own AI work in one person — what started as a prototype has become a tool I use every day and against which I test my own products.

• Led the end-to-end delivery of enterprise full-stack web applications by driving requirement analysis, solution design, frontend and backend development, database design, API integration, code reviews, team coordination, Agile execution, CI/CD deployments, production support, performance optimization, security implementation, and stakeholder collaboration to deliver scalable, high-quality software solutions.

• Led development of RunBot AI assistant autonomously using LLM-powered workflow automation (React, TypeScript, Java, MongoDB, NATS)
• Architected TMS platform providing unified transportation management and real-time logistics visibility with AI processing pipelines
• Designed event-driven microservices architecture supporting marketplace
• Drove architectural decisions and technical leadership across full-stack platform development

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

• Built custom Yocto Linux image with Docker support (NXP i.MX 6ULL)
• Developed distributed Python application (web interface, gas/temp control)
• Designed multiple docker containers for production and development
• Wrote documentation per IEC 62304

• Developing a multi-class classification model to predict plant composition and its spatial and temporal changes using predictors, including satellite images, climate time series, and other environmental data such as land cover, human footprint, bioclimatic, and soil variables.
• Developing recommender systems using contextual bandits for an e-commerce platform.
• Building deep neural network models that predict flood-affected areas.

• Comprehensive strategic and technical development of three key suppliers

• Conduct data management and statistical analysis for clinical studies on behalf of CROs.
• Guest lecturer at Ivancity University, Paris, specializing in data anonymization techniques and statistical disclosure control.
• Provide scientific and medical writing services for pharmaceutical companies.
• Perform optical mapping data analysis and develop software tools with a focus on algorithm optimization and technical support.

• Developed a retrieval-augmented generation (RAG) application using LangChain and LangGraph for corporate document parsing, delivered as an installable Electron desktop application with local AI models via Ollama.
• Currently providing ongoing AI feature support for the Loan Pricing Tool at Hamburg Commercial Bank, with a commitment of three days per month.
• Architected Kubernetes-native solutions, including Helm chart configuration and Azure DevOps pipeline integration.

• Handle probate matters, distribute business interests, and oversee the transition or dissolution of the company depending on the operating agreement.

• Reviewing the operating agreement: determining what happens to the interests - transfer, buyout, or dissolution.

• Valuing the business interest: obtaining a fair market valuation of the ownership share to distribute assets or facilitate buyouts.

• Managing business operations: ensuring employees, vendors, and clients are informed and the business continues to run smoothly during the estate process.

• Protecting assets: safeguarding company property, intellectual property, and financial accounts until they can be legally transferred or distributed.

• Organizing potential general service requests and/or warranty claims and their settlement and necessary reserves.

• Developing an app that reflects the stock portfolio
• Environment: Laravel 12, PHP 8.4, MySQL, Git, IntelliJ, GitHub, AlpineJs, TailwindCss

• Design of requirement verification based on the INVEST principle
• Implementation of the prediction model with scikit-learn and BERT
• Implementation of the web client with ReactJS and FastAPI
• Adaptation of the T5 model to improve user story generation according to the INVEST framework
• Certification of NLP and scikit-learn
• Technologies: Python, NLP, Scikit-Learn, BERT, T5, ReactJS, FastAPI, Cursor Visual Paradigm, Visual Studio, Draw.io, NSIS, vite, Electron