npm Experts in Germany

• Recurring problem in my own AI-assisted projects: requirements analysis, use cases, and architecture decisions can be created quickly with AI support, but remain difficult to follow and scattered across Markdown files – knowledge is lost as soon as it is no longer in the context window. arknet turns requirements engineering and architecture knowledge into structured, verifiable data instead of plain text: requirements, use cases, and architecture decisions form a consistently linked knowledge graph, traceable from requirement to architecture decision – queryable by both people and AI agents. Technically based on RDF/OWL and a custom MCP server.

• Result: Working MCP daemon, Docker image published automatically to GHCR, nine hexagonal modules, eleven ADRs (including an Open-Core licensing model). Requirements engineering and Ubiquitous Language hexagons are active. Public as a Community Edition under Apache-2.0 since 07/2026 (github.com/kogn-io/arknet), together with the Claude Code plugin and GHCR image; Open-Core model.

• Label: Java, Maven, RDF, RDF4J, OWL, SPARQL, Model Context Protocol, Spring AI, Docker, GitHub, Git, Claude Code, Obsidian, DDD, Hexagonal Architecture, ArchUnit, JUnit, AssertJ, Interface Development, Software Architecture, Continuous Integration, Knowledge Management

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

• Implementing and extending an Electron app based on TypeScript, React and Node.js to display stream content and technical data
• Extending a Kotlin backend for message processing via Kafka
• Extending various React modules
• Programming custom solutions for customers, including testing
• Creating documentation
• Development in accordance with Scrum processes

Used skills: React, React Hooks, Jest, Vitest, Typescript, Electron, IntelliJ, Vite, Github, Jira, Node.js, yarn, npm, pnpm, Swagger, OpenAPI, Storybook, Docker, Prettier, Eslint, tailwindcss, i18n, GraphQL, CoPilot, Postgres, JSON, Sqlite, trpc, influxdb, Java, Spring, Kotlin, Kafka, Git, Sonarcube

• Developed cloud-native enterprise applications on SAP Business Technology Platform using Node.js, SAP UI5, and RESTful APIs, delivering solutions across training management, procurement, employee information, and logistics domains
• Served as the primary developer for the maintenance, enhancement, and production support of three enterprise applications, delivering new features, resolving production issues, and coordinating releases with business stakeholders
• Experienced in leveraging AI-assisted development tools such as Microsoft Copilot to accelerate feature development, generate code, prototype solutions, and support application migration and modernization
• Designed backend services, domain models, and SAP Fiori/UI5 interfaces, implementing business workflows, role-based access control, validations, scheduling, reporting, and data import/export capabilities
• Designed and integrated enterprise services with SAP SuccessFactors, SailPoint, ERP systems, and external Learning Management APIs, including automated synchronization for 11,000+ user data
• Designed and implemented AMQP-based event-driven services processing up to 500 RFID parcel scan events per day for a logistics application
• Managed deployments and application operations using CI/CD pipelines, SAP Solution Manager, SAP BTP Cockpit, Kibana, and cloud monitoring tools, performing root-cause analysis and resolving production incidents
• Managed application dependencies by resolving npm package version conflicts and remediating critical and high-severity security vulnerabilities, ensuring production compliance and application stability
• Collaborated with architects, business users, SAP governance teams, and distributed Agile teams throughout technical design, code reviews, sprint planning, documentation, and software delivery

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

• Development and optimization of the RTL+ frontend application for SmartTV and set-top box platforms with React and Next.js.
• Key role in the technical coordination of developers within the team and in coordinating implementation.
• Central interface to adjacent teams to simplify development processes and improve cross-team alignment.
• Improved frontend performance, stability, and rendering behavior on low-powered devices in a restricted runtime environment.
• Implemented a frontend testing strategy with Jest, React Testing Library, and Playwright.
• Implemented accessibility improvements according to WCAG 2.2 and WAI-ARIA.
• Integrated Didomi Consent Management as a contribution to increasing ad monetization on streaming platforms.
• Used AI-supported engineering workflows with Cursor for structured implementation, refactoring, and faster problem solving.

Technologies used: React, Next.js, TypeScript, JavaScript, GraphQL, Apollo Gateway, Zustand, Tailwind CSS, Styled Components, React Testing Library, Playwright, Jest, HTML5, CSS3, AWS Lambda, EC2, CloudFront, S3, GitLab CI/CD, NX, Cursor

Development of an iOS app for virtual try-on and outfit suggestions

The goal of the project is to develop a mobile application for personalized, photorealistic outfit suggestions. Users should be able to upload their own photos, try on clothes virtually, and find products that can be bought directly in the generated suggestions.

• Planning and implementation of the onboarding and photo upload in the iOS app
• Development of the mobile application with Expo and React Native
• Implementation of a Hono/Node.js backend for user, product, and generation processes
• Building an asynchronous processing pipeline with BullMQ and Redis
• Connection of PostgreSQL/pgvector and S3 for product, image, and generation data
• Integration of Gemini and OpenAI for outfit generation and image processing
• Implementation of a credit system and integration of RevenueCat
• Integration of Stripe Connect and affiliate product feeds for products that can be bought directly

Label: TypeScript, React Native, Expo, Hono, Node.js, PostgreSQL/pgvector, BullMQ, Redis, S3, Gemini, OpenAI, RevenueCat, Stripe Connect, Docker

• Developed a React and TypeScript dashboard with reusable UI components and API-driven data visualization.
• Implemented dynamic data rendering, state management, and performance-focused frontend architecture.
• Integrated Python-based backend services for processing and visualizing SEO analytics.

• 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

• 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.

• Developed an accessible, responsive website based on Figma designs for a major sports event in compliance with WCAG, BITV and EN 301 549
• Planned and set up the tool stack with Vite, Playwright, Docker and GitLab CI
• Worked on two existing projects (Vue.js & Nuxt), focusing on bug fixing, accessibility audits and developing new features
• Collaborated with Design and QA to consistently implement accessible UI patterns
• Advised on improving existing frontend architectures in terms of accessibility, performance and maintainability

Working as a full-stack (next.js, Postgres) engineer and consultant to build the core platform with underlying services for location-based comparisons and requests. I’m working on performance optimization across the stack (especially Postgres queries) and writing product specifications and the platform architecture with another colleague.

• Tech stack: Python, Qt, tensorflow.js, plotly, Angular, TypeScript, HTML, CSS, Git

Project: Intelligent Light Communication Software — Audi

• Analysis and clarification of system requirements with the customer and translation into software architecture and design decisions
• Architecture and implementation of CAN FD and SPI communication on NXP S32K312
• Design and development of flash bootloader, flash driver, and boot manager for secure OTA-capable updates
• Configuration of the AUTOSAR BSW architecture (Dcm, Dem, NvM, BswM, Os, Mcu, Port, Com stack, Rtc) for portability and maintainability
• Design of the crypto stack (Csm, CryIf, Crypto) for secure flash and diagnostic data; integration of the NXP HSE core and wrapper layer
• Integration of customer-specific modules (Sfd, Ivd, Npm) into the Vector AUTOSAR stack
• Definition of the memory architecture: Memmap, CMake, and linker script configuration
• Leading board bring-up for the Audi light demo platform; implementation of diagnostic routines and identifiers