OpenCode Experts in Germany

• Marketing Strategy: Lead the end-to-end analysis and evaluation of cross-channel marketing campaigns across the entire Customer Journey. My focus is identifying optimization potential and deriving clear, actionable recommendations that drive measurable business impact.
• Data Science & AI: Advanced predictive modeling (Churn, LTV), market basket analysis, clustering, and real-time AI-powered audience discovery utilizing RAG/LLMs.
• Marketing Analytics & Measurement: End-to-end attribution analysis, Marketing Mix Modeling (MMM), audience segmentation, conversion path analysis, and A/B testing across all major platforms.
• Data Engineering & Reporting: Designing and managing robust, multi-platform data pipelines (BigQuery, GCP) for data consolidation, automated dashboard generation, and critical API integrations.

• 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

• Used OpenCode and AI-assisted software engineering to design, implement, refactor, test, and document an end-to-end RAW/SDTM/ADaM pipeline in R for Dr. Falk Pharma (07/2026), including metadata-driven transformations, automated validation rules and QC, traceability, and reproducible clinical outputs.

• Self-employed · Berlin, Germany
• Co-founded the company and own the entire technical side: product architecture, backend, frontend, infrastructure and operations.
• Designed and built the Automated Booking System (ABS) as well as the core platform and payment logic.
• Development of AI-powered SaaS products, from architecture through backend and frontend to production operation.
• Technical consulting on product architecture, data protection and permissible automation.
• Building, running and monetising my own API products for AI agents, each available as a REST interface and as an MCP server.
• Full ownership of architecture, infrastructure, billing, legal texts and go-to-market.

• Drive migration of enterprise authorization platform from Styra DAS to open-source OPA via Skipper (Zalando's Golang-based ingress proxy) integration
• Optimise k8s resources and integrate native Prometheus metrics with OPA
• Migrate from internal monitoring solution to Prometheus CRs + Dash0

Tech Stack: Java/Kotlin, Golang, Python, Spring Boot, AWS, Kubernetes, Docker, OpenTofu, Prometheus, Grafana

• Concept and full-stack development of an app for parking space booking & management (Hahn Airport)
• From requirements to implementation and deployment; AI-supported development (Claude Code)

Conventional Paradigm Test (CPT) – AI Evaluation & LLM Research

Development of an experimental evaluation approach to examine “paradigmatic closure” in Large Language Models — that is, the question of how far LLMs can recognize the basic assumptions, values, and limits of the paradigms within which they generate answers.

Design and testing of an additional approach to classic AI benchmarks that does not primarily measure factual correctness or task performance, but instead examines a model’s ability to recognize alternative perspectives, make implicit assumptions visible, and reflect on the limits of its own answer or interpretation framework.

Focus areas: development of evaluation criteria and test questions · LLM evaluation and comparative model analysis · prompt and response analysis · qualitative classification of model answers · study of epistemic compression and value leakage · benchmark and literature research · development of structured assessment and analysis methods

As part of CPT, existing AI evaluation approaches and benchmarks were analyzed, and a minimalist test protocol was developed that classifies model answers by response patterns such as DIRECT, CLARIFY, PLURALIST, REFUSE, and META-AWARE. TruthfulQA was used as the basis for experimental application and comparison with existing reference answers.

Technologies & Methods: Large Language Models (LLMs) · Generative AI · Prompt Engineering · AI Evaluation · TruthfulQA · Benchmark Analysis · Human-in-the-Loop Evaluation · Qualitative Content Analysis · Research & Literature Review

Internal systems with regulatory and security requirements could not be used directly by AI tools for incident triage, troubleshooting, and documentation search. The goal was to securely integrate these systems through MCP while preserving existing acce...

As a freelance employee / independent consultant, I supported a wide range of development projects and advised clients on digital innovation initiatives. A common role was acting as project manager / product owner at the interface between the client and the development team.

• Product Consulting — (Fractional) Product Owner, Freelance Product Management
• AI Services — AI consulting, training, vibe coding / agentic engineering, AI agents
• Tech Services — full-stack web development, design/UX, MVP delivery.

Worked as an App Engineer as part of the IoT Control team in a React Native Stack.

• Implementing new Components based on the Tonies Design System.
• Improving, extending and maintaining Tonies Design System
• Adding new features like Volume and Playback Control of the Tonies
• Fixed connection issues via bluetooth and wifi
• Removing technical debt and polishing for an upcoming big software and hardware release
• Improving accessibility by optimizing screens and components for usage via screen readers.
• Wrote lots of automated tests to ensure app quality is always stellar.
• Weekly app releases in a high volume workload environment

Results & Impact:

• Improved app stability and connection reliability ahead of a major software and hardware release
• Raised overall app quality through a significantly broader automated test suite, catching regressions before they reached users
• Made the app usable with screen readers, improving accessibility for a wider audience
• Sustained a weekly release rhythm in a high-volume production environment without quality regressions

Technologies: react-native, expo, typescript, react-19, react-compiler, react-navigation, zustand, @tanstack/react-query, i18next, figma, app-store, play-store, sentry, bitrise, config-cat, poeditor

• Building an AI & Data Consultancy Practice with the goal of helping European companies adopt Artificial Intelligence and modern data platforms
• End-to-end further development of a production system using modified coding agents (OpenCode). Tech stack: Kubernetes, Argo, Keycloak, Typescript, Grafana, GitOps, DevOps, Playwright
• Internal research project on the use of coding agents in the field of mathematical logic for creating formal models. Use of Cursor IDE and Codex, Codex CLI. Architecture design, quality control and refactoring, as well as writing code and tests. Repository (open source) available pre-launch
• Research on the role of mathematical logic as a formal language that connects IT and AI with business processes
• Project lead for collecting and deploying parking recommendations for rail vehicles with significant savings potential based on real-time data in a mobility and transport company
• Project lead for collecting and distributing process measurement points for real-time control in a mobility and transport company
• Deputy application owner for an app used for communication in the dispatching and provision of rail vehicles

• Leading the product lifecycle for sovereign AI platform and operating system teams for enterprise & government clients and internal stakeholders (infra, solution delivery, support, revenue)
• Built and scaled the platform from a 200-user beta to a full rollout of 70K+ members at the Bundesagentur für Arbeit (BA), secured with ISO 42001 and EU AI Act compliance
• Architected the shift to a multi-tenant shared inference, increasing GPU cluster utilization from 20% to 85% and reducing infrastructure cost-to-serve by 40% for SaaS clients
• Shipped model quantization, allowing clients to run advanced LLMs on legacy hardware (A100s GPUs) instead of the H100s, saving upwards of 70% cost per enquiry
• Abstracted complex Helm configurations into a dynamic model manager, reducing the time to install or swap models by ~80%
• Killed an expensive move to build own dashboard service, pivoting to an API-first data strategy that clients can consume directly and saving €100Ks in opex and capex
• Built a safety-first agent marketplace and control plane lighthouse project for a Tier-1 bank, allowing internal teams to deploy autonomous agents within strict regulatory guardrails