GitHub Copilot Experts in Germany

Project goal: Carrying out system tests and validating industrial communication and control systems, including requirements definition and verification.

Responsibilities:

• Test planning, test execution
• Test strategy, test cases, and test specifications
• Requirements analysis
• Ensuring traceability between requirements, test cases, and defects
• Carrying out regression and integration tests
• Defect analysis
• Simulation and validation
• NetSniffer Wireshark
• Supporting test automation (Python, CI/CD)
• Reporting
• Stakeholder coordination and agile collaboration (Scrum / SAFe / Kanban)
• V-Model
• CI/CD automation with Python, Groovy, and frameworks (Selenium, PyTest)

Technologies:: CAN, Modbus, Ethernet, PLC, PROFINET, Codebeamer ALM, Scrum, SAFe, MS Teams, Git, CI/CD with GitLab CI and TeamCity, Windows Batch, FAS, Wireshark, Python, Enterprise Architect (EA), AI tools (e.g. ChatGPT, Microsoft Copilot), VS Code, Tia Portal, SCL, Python (Selenium, PyTest)

• Team leadership: Prioritization and coordination of four cross-functional teams.
• Platform strategy: Development and implementation of strategies to optimize existing IT platforms.
• Stakeholder management: Active management of expectations and communication with internal and external stakeholders.
• Program and innovation management: Prioritization and coordination of cross-department projects as well as innovation initiatives.
• Product Owner consulting: Advising Product Owners with a focus on product development and continuous product improvement.
• Organizational development: Improving communication and decision-making structures across all organizational levels.
• Change management: Implementing best-practice change management methods to ensure continuous optimization and innovation.
• Quality assurance: Ensuring high quality standards in processes, services, and deliverables.

Workflow-automation SaaS for operations teams (Berlin, 120 people); full-time freelance engagement reporting to the CEO: an initial 12-month interim mandate, extended twice through the AI build-out; owned product for one squad and coached the other product managers on process.

• Led generative AI (LLM) integration into the core product: from LLM-powered steps to natural-language workflow authoring and step-level automation suggestions, plus AI-managed dynamic workflows, shipped behind eval gates with human-in-the-loop fallbacks: AI-drafted workflows grew to 31% of all new workflows, and median time-to-first-workflow fell from 3 days to 4 hours.
• Packaged the AI capabilities as a usage-based add-on priced on executed automation steps, working with sales and marketing on positioning: ~€800K added ARR in the first year, and adopting accounts churned 1.8 pp less.
• Owned the roadmap end to end: replaced feature-request-driven quarterly planning with an outcome-based rolling roadmap built on quarterly bets and explicit kill criteria, presented monthly to the executive team and quarterly to the board.
• Rebuilt the product-management operating system: weekly customer-discovery cadence incl. workshop facilitation, RFC/decision-doc reviews and a single quarterly metrics narrative; coached four product managers, one promoted to senior during the engagement.
• Closed the engagement as scoped: hired and onboarded the permanent VP Product, handed over the process playbook and roadmap, and exited on schedule in June 2026.

• Designed and developed a multi-tenant SaaS platform enabling organizations to build their own knowledge bases and chat with brand-customized AI assistants (white-label approach with dynamic branding per organization).
• Implemented a scalable RAG architecture with a GPT-4o tool-use loop, hybrid semantic search, and strict tenant isolation at database and search index level.
• Built persistent, project-like chat sessions including a streaming API (SSE), multilingual support, and speech input/output (STT/TTS).
• Delivered the cloud infrastructure as Infrastructure-as-Code, fully automated per-customer CI/CD pipelines, and an onboarding process for new tenants.

Technologies used: Python, FastAPI, Pydantic (v2 noted), Next.js, React, TypeScript, Tailwind CSS, OpenAI / LLMs (GPT-4o), Azure AI Search, Cosmos DB, Azure Blob Storage, Azure Cognitive Services Speech, Azure App Service, Azure Container Registry, Retrieval-Augmented Generation (RAG), Server-Sent Events (SSE), Docker, Terraform, GitHub Actions, REST, OpenID Connect (OIDC), Multi-Tenancy

• Own the 12–18 month roadmap and key outcomes for Elli's enterprise customer platform, covering onboarding, pricing, billing, analytics and broader platform modernization; redesigned the Fleet onboarding funnel to double conversion, supporting a projected €20.7M revenue uplift by 2028.
• Lead the broader Energy Intelligence product and directly own its AI/ML, asset and portfolio-optimization capabilities, including MLOps and safe strategy deployment, strategy lifecycle management and backtesting; delegated data and V2G integration roadmap ownership to a new PO as the platform scope expanded.
• Built a Human-in-the-loop GenAI/RAG support workflow, increasing L1 resolution by 24%, routing accuracy to 91%, and reducing L2 workload by 30%.
• Introduced standardized data contracts and a self-service Python toolkit for traders and Data Scientists, increasing platform adoption by 15% and reducing support effort by 50%.
• Built and scaled a real-time orchestration product from 32 to 3,000+ endpoints across four markets, growing recurring revenue from €1.4k to €56.3k MRR.
• Developed product and AI capability across the organization, training 20 PMs on RAG, agents and prototyping; mentoring a junior PM and coaching an Enterprise Platform Tech Lead toward Product Management ownership.

IT consulting, analysis, architecture design, new and further development, code review, test automation, continuous integration, continuous delivery in backend and frontend areas for Automotive Project Instavalo.

Frontend:

• Implementation of UI components according to specifications, especially style guides and responsive design eith React and Typescript
• Component testing
• Code documentation
• CI/CD with Gitlab Pipeline

Backend / IoT:

• Analysis and architectural design with AWS Greengrass IoT on Edge Devices
• Setting up Microservices containers with Docker Compose on Edge device with AWS Greengrass and AWS IoT IAM, Token Exchange Service, Ansible
• CI/CD with Gitlab Pipeline, Terraform, AWS ECR
• Logging with Fluentbit Lua Language for AWS Cloudwatch
• Python Lambda for AWS Greengrass Recipe deployment on Edge Devices
• Implementation of test-driven development with JUnit, Mockito, and code Coverage
• Jacoco
• Definition of REST interfaces with OpenAPI / Swagger
• Development and enhancement of software based on Java Quarkus, Typescript NestJs NodeJs and Python
• Authentication and authorization in Aws IAM
• Development of REST and gRPC interfaces for the frontend and backend
• Implementation of Maven dependencies with DevSecOps OWASP
• Spring AI, Jetbrains AI Assistant, Junie, Github Copilot, Claude Code, Agents, Skills, Command, Hooks, Subagents

Designing AI-native digital products by combining product strategy, UX research, interaction design, software engineering, and modern AI workflows. Leading projects from discovery to implementation while integrating AI throughout the entire product development lifecycle.

Key responsibilities

• → Product discovery, stakeholder workshops, Jobs-to-be-Done and user research
• → User journey mapping, information architecture and interaction design
• → Wireframes, high-fidelity UI, prototypes and scalable design systems in Figma and Penpot
• → AI-assisted interface generation and rapid concept exploration using Figma AI, Figma Make and generative design workflows
• → Design-to-code workflows with AI-supported frontend generation and engineering collaboration
• → Building accessible interfaces following WCAG 2.2 and enterprise design standards
• → Usability testing, iterative validation and KPI-driven product optimization
• → Development of AI knowledge systems, MCP-powered design workflows and human-in-the-loop review processes
• → Close collaboration with engineering teams to ensure production-ready implementation

• Designed role-based delivery assignment workflows, switchable between own fleet and partner carriers, with traceable status chains from „pending“ to „in delivery.“
• Designed AI-assisted route optimization, where dispatchers review drive-time-optimized route suggestions as drafts and apply them in one click.
• Designed a central planning interface for delivery and route management, bringing table view, map view, and route composition into a single workflow.
• Built interactive prototypes to align new product features early with stakeholders and engineering.

Key methods: AI-assisted Product Design, Workflow Design, Role-Based Workflows, Dashboard Design, Interaction Design, Prototyping, Logistics/Operations UX, Stakeholder Collaboration

• Supporting the DevOps team in Terraform-managed, multi-region AWS infrastructure to achieve environment parity.
• Developed end-to-end CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy, automating the build and deployment.
• Maintained pre- and post-deployment scripts to automate critical tasks such as database schema migrations and environment sanity checks.
• Implemented CI/CD flow specifically for hotfixes via separate Git branches, managing back-merge activities from feature branches to release branches to ensure code integrity through automated conflict resolution.
• Deployed a dedicated, lightweight sanity check application hosted cost-effectively on Azure Container Apps to run automated health and basic functional checks as a post-deployment activity triggered via pipeline.
• Investigated production incidents through code changes and AWS CloudWatch logs.
• Coordinated integration of Dynatrace APM and its APIs for monitoring purposes.
• Full stack QA strategist for a high-traffic e-commerce platform built on a layered architecture for the back-end testing of core platform services, especially the order management system in Zed and Glue layers.
• Managed automation activities, testing process, and refactoring practices.
• Responsible for framework migrations, setup, and training for new automation frameworks.
• Promoted a shift-left approach within the QA team and created the test concept.
• Participated in meetings with IT managers, business owners, product owners, and team members.
• Designed and implemented contract testing to validate API schema compatibility between the order management system and the Zed and Glue layers, reducing production-relevant breaking changes by approximately 3%.
• Led the migration to a multi-environment framework that enabled test execution across 4 country configurations from a single codebase.
• Integrated automated unit and functional tests directly into the GitLab CI/CD pipeline, reducing pipeline runtime by 32%.
• Coached and trained 5 QA engineers across Germany and Hungary in test automation, framework architecture, and best practices.
• Architected a layered backend test automation framework separating business logic, API request builders, and the database layer.
• Piloted AI-assisted testing with Playwright Agents, the Playwright MCP Server, and GitHub Copilot for automated test generation, execution, and self-healing Playwright scripts.

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

• ▶ Built real-time voice assistant (STT → LLM → TTS pipeline) benchmarking and evaluating multiple STT providers including faster-whisper and Azure Speech. achieved sub-3s latency, Groq API (Llama 3) with multi-turn memory - directly handling edge cases in dictation, names and passcode recognition.

• 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.

• 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.

AI Platform Backend – Senior Developer

Brought in to design and build a backend for an AI platform from scratch, including multi-provider LLM orchestration and real-time infrastructure for AI influencer personas at scale.

Tasks and responsibilities

• Architecture and implementation of a multi-LLM orchestration layer with Semantic Kernel to integrate GPT-4 and other providers for core platform logic and AI influencer personas, reducing model-switching overhead by abstracting provider APIs behind a single interface.
• Design and development of a backend from scratch in C# / .NET 10, including domain modeling with DDD, a versioned RESTful API layer, and cloud infrastructure setup on Azure.
• Built a real-time chat infrastructure with Server-Sent Events (SSE), message persistence, and delivery guarantees for live operation of AI influencer personas at scale.
• Developed a media management service with integration of cloud object storage for upload and retrieval of influencer-generated content.
• Created an integration and unit test suite with data seeding for reliable regression testing across all core platform flows, significantly reducing production error rates.

Tools and technologies: C#, .NET, ASP.NET Core, Python, TypeScript, MySQL, Semantic Kernel, EF Core, Minimal APIs, LLM Orchestration, Prompt Engineering, Agentic AI, Generative AI, AI-Assisted Engineering, Claude Code, GitHub Copilot, Google Gemini, OpenAI API, Ollama, Redis, Azure, Azure Container Apps, Azure Database for MySQL, Docker, GitHub Actions, Clean Architecture, Vertical Slice Architecture, CQRS, Domain-Driven Design, REST API, xUnit, Integration Testing, Unit Testing, Jira, Confluence, Scrum