Software Developers in Germany

• Built a customized MediaWiki instance, including installation, MySQL database, SSL, and automatic backups
• Set up user roles (Admin, Mod, Verified, User) and a permissions system
• FlaggedRevisions for editorial review workflows · Commenting and rating extensions

• Technical leadership across hardware, firmware, and software teams; scope: hardware/firmware team (4 people) and leadership group (5 people)
• Consolidated and documented a product family that had grown over more than 15 years and aligned it with CRA compliance — from the bare-metal I/O module to the cloud interface.
• Provided the most important customer product with the essential requirements and architecture documentation within two months — for a firmware landscape that had grown over more than 15 years. It now supports the customer’s modernization strategy.
• Established a monthly reporting line to the supervisory board and executive board within three months: nine meetings since 12/2025. The report itself is versioned and built from the CI pipeline; it is based on automatically collected activity and release data instead of assessments.
• Built a container-based CI/CD infrastructure from scratch: cross-compilation, host tests, and documentation builds in one continuous pipeline.
• Introduced declarative QA gates for DevOps and development artifacts — from the start using lefthook instead of pre-commit, executed in a dedicated container image.

Technologies used: arc42, req42, tpo42, docToolchain, PlantUML, ArchiMate, C4 model, ADR, C, C++ (GTest), CMake, Bare Metal (ARM Cortex-M3/M7), OCI containers, Jenkins, lefthook, Prometheus, Grafana, SBOM, CRA, OPC, SCADA, PLC integration, IPv6 migration, Zero Trust, Sociocracy 3.0, Cynefin

Built an international e-commerce platform for a multi-vendor marketplace for digital assets from scratch. Designed and operated cloud native architectures at enterprise scale.

• Designed and operated a highly scalable microservice and serverless architecture
• Built the complete cloud infrastructure with Terraform + AWS CDK in AWS
• Provisioned ECS/EKS clusters (Fargate), Application Load Balancers (reverse proxy), and Lambda functions
• Observability & tracing with CloudWatch, DataDog, Prometheus, and Grafana
• End-to-end setup with DataDog (formerly AWS CloudWatch), Prometheus, and custom Grafana dashboards
• Integration of advanced metrics (including ORM mapper) and distributed tracing with Jaeger
• Robust backup and disaster recovery strategies
• RDS Postgres backups and hourly snapshots
• Read-only, asynchronously synchronized replicas with automated master failover in emergencies
• Minute-level rollback capability through versioned Docker images on ECS and Git-based CI/CD pipelines
• Created CI/CD pipelines with GitHub Actions for automated multi-stage deployments (Dev, Testing, Prod)
• Integrated Stripe for international payment processing
• Built a marketplace payment system with multiple parties and payout routines
• Used Algolia for high-performance real-time search of digital assets on the platform
• Federation of services with GraphQL and Hasura
• Later migration to GraphQL Mesh
• Test Driven Development (TDD) - unit, integration, and E2E testing with Jest, Vitest, and Playwright
• Used Next.js / React for modern frontend applications in the nx monorepo
• Enterprise security architecture & access control
• Integration of JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA protection, and secret vaults
• Authorization concepts with RBAC, ABAC, and native Postgres Row-Level Security (RLS)
• Built internal microfrontends with Retool for fast prototyping and operational business processes

Technologies: ABAC, AWS CDK, AWS CloudWatch, AWS ECS, AWS EKS, AWS Fargate, AWS RDS, AWS S3, Algolia, Auth0, DataDog, Docker, GitHub Actions, Grafana, GraphQL, GraphQL Mesh, Hasura, JWT, Jaeger, Java, JavaScript, Jest, Kotlin, Kubernetes, Monorepo, Next.js, OIDC, Playwright, Postgres, Postgres RLS, Prometheus, RBAC, Redis, Retool, Serverless, Stripe, Terraform, TypeScript, Vitest

• Planned and developed a CPU monitoring application for monitoring system performance and resource utilization.
• Designed and implemented a Spring Boot backend providing a REST API for processing and exposing monitoring data.
• Developed the React frontend for presenting monitoring information in a clear and user-friendly interface.
• Integrated PostgreSQL for persistent storage and management of application data.
• Containerized the application and its services using Docker Compose.
• Automated infrastructure provisioning and deployment using Terraform on AWS.
• Structured the application as a modern, maintainable system using REST-based communication between frontend and backend.
• Designed and developed a secure, scalable CPU monitoring architecture (cpu-watcher) with a dedicated collector application that streams monitoring data to the backend, reducing direct exposure of system resources.
• Designed a secure cloud infrastructure with the database isolated within a private network and OIDC-based authentication.
• Implemented Infrastructure as Code with Terraform and integrated version-controlled CI/CD pipelines to automate testing, infrastructure changes, and application deployments.
• Designed and implemented the frontend delivery architecture using AWS CloudFront.

Stack: Spring Boot · React · PostgreSQL · REST API · Docker Compose · Terraform · AWS

• Techstack: Next.js, React, Typescript, ChromaDB, Embedding Models, OpenAI API
• Developed an AI-based matching system for a recruiting company for targeted candidate search in over 370,000 LinkedIn profiles
• Architected Next.js frontend, ChromaDB as vector database, BGE-ICL for embeddings and GPT-4.1 for semantic search via tool calls
• Automated manual pre-selection to enable finding qualified candidates in seconds
• Managed three Linux Ubuntu servers for clients with open source software based on Docker containers

• 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

• Task Engineering: Evaluating Coding Agents.
• Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
• Prompting & Translation: finding failure points where AI does not work, in German.
• Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
• Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
• Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
• Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.

• Modernization of a large-scale Java enterprise application*

The project is modernizing a complex enterprise application that has grown over many years. The existing Spring-based legacy system runs on Java 8, OSGi, and Eclipse RCP and is being gradually migrated to a modern, maintainable architecture with Java 25 and Quarkus.

Marcus works on analysis, architecture, refactoring, and implementation. One focus is on untangling historically grown structures and dependencies and on building a clean, sustainable Java and Quarkus technology stack.

Tools & technologies: Java 8, Java 25, Quarkus, Hibernate ORM with Panache, EclipseLink, OSGi, Eclipse RCP, Maven, JUnit, Mockito, REST, JSON, Git, Eclipse IDE, IntelliJ IDEA Ultimate, Jira, Confluence

• Analysis of the existing CAN communication between microcontrollers
• Analysis of the sensors used and the measured values collected
• Planning the CAN messages for transmitting the measured values
• Iterative adjustment of the microcontroller code to the new CAN messages
• Cross-compilation from x64 to arm64

• Further development of the existing e-commerce platform based on SAP Commerce (Hybris) to meet the growing demands of digital commerce.
• Ensuring the scalability and performance of the backend, so the platform remained stable and efficient even under heavy user load.
• Development and integration of new OCC REST APIs and services for modular extensions and flexible adjustments, to implement new features quickly.
• Optimization of data flows and interfaces, which significantly improved platform efficiency and system performance.
• Ensuring a maintainable and scalable code base by using Clean Code principles, proven design patterns, and a future-proof architecture.
• Reduction of errors through extensive testing with JUnit, Mockito, and load tests with Gatling, supported by the introduction of automated test processes.
• Improved system performance through targeted refactoring measures and efficient database queries, especially to handle peak loads.
• Use of modern cloud and monitoring tools such as Kubernetes, Google Cloud Platform (GCP), and Grafana to ensure a stable and monitored infrastructure.
• Clear improvement in efficiency, scalability, and reliability of the platform, which now meets the demands of a dynamic and growing e-commerce market.

• Development of safety-related embedded software for a mobile machine on a Hydac TTC 2390 controller.
• Implementation in C with consideration of SIL 3 / ASIL D and MISRA-C:2025.
• Implementation of communication via CAN, CANopen, and J1939.

Standards, guidelines and norms: ISO 26262, IEC 61508, MISRA-C:2025

Technologies: C99, Hydac TTC 2390, Infineon TriCore Aurix TC397, Hightec C/C++ Compiler, PC-lint Plus, CAN, CANopen, J1939, MISRA-C:2025

• Optimizing and accelera­tion of our Gitlab CI pipeline

• Conceptual work for the PoC of the Zero Trust system

• Extension of the policy-engine backend in Go

• Extension of the policy-testing mechanism in Python

• Architectural design of the PEP component of Zero Trust

• Documentation of the product

• Technologies: Zero Trust, Go, Python, Gitlab CI, Docker, JWT, Domain-Driven Design

• 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.

• 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