GitHub Copilot Experts in Germany

• 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.

• 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

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

• 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.

• Analysis of the existing reporting platform including processes and governance topics with stakeholders from sales and marketing.

• Detailed analysis and evaluation of client-defined requirements for existing reporting and new dashboards.

• Supporting stakeholders in managing sales processes and early detection of KPI trends.

• Use of Microsoft Power BI as central analysis and reporting platform.

• Developing a proposal for the necessary evolution of processes and the Power BI platform.

• Gathering current business processes and defining company-wide KPIs in coordination with stakeholders.

• Analysis and inventory of the client's Power BI platform.

• Analysis of processes and data governance.

• Recording and documenting current business processes.

• Developing recommendations for process and reporting platform improvements.

• Designing and implementing dashboards in Power BI.

• Defining company-wide KPIs and aligning them with stakeholders.

• Microsoft Power BI.

• Data analytics.

• KPI definition and reporting.

• Dashboard design and data visualization.

• Stakeholder management and requirements management.

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

• Architected and implemented 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.
• Designed and developed 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 the production error rate.

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

• ▶ 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.

• Governed multi-agent orchestration for regulated, EU-based companies – self-hostable, compliant with the EU AI Act and GDPR („by design“), BYOM (own models/GPU).
• Two-gate governance: agent deliberation + mandatory human approval, full signed audit trail; graduated autonomy model („internal → autonomous per skill“).
• Verified knowledge graph („Company Brain“) with source evidence for every answer; own orchestration framework (Virtual Team Framework).
• Industry solutions for financial services: compliance monitoring, invoice and contract review; hands-on development with LLMs (including Anthropic/Claude), agentic workflows, RAG.
• Building the governance-focused multi-agent platform TeamIntel (see AI reference projects).

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

Conceptual design and implementation of a modular customer portal based on Laravel.

The focus was on defining a maintainable system architecture with broad use of Domain-Driven Design principles (within the Laravel architecture), introducing automated quality assurance processes (test strategy, CI integration), and preparing an auditable operation (logging, traceability of changes) in an AWS-based infrastructure, taking IT security standards according to NIST and process requirements according to ISO 9001 into account.

Achievements:

• Analysis and structuring of business requirements in close coordination with stakeholders
• Documentation of the system architecture and infrastructure incl. change and release management
• Design and implementation of an interface for integrating SAP systems
• Planning and implementation of automated tests for quality assurance
• Implementation of security and compliance requirements, including SBOM generation, software license management, and QA processes
• Technical consulting and support for the internal IT team
• Introduction and establishment of AI-supported development processes (Spec-Driven Development), including AI-readable specifications, integration of AI instructions into the development environment, and training developers for productive use

Technologies and tools: SAP, Docker, ddev, PHP 8.4, Laravel, Filament, C4 Model, Architecture Decision Records (ADR), Mermaid, PlantUML, Spec-Driven Development, Claude, GitHub Copilot, Codex

• Lecturer for the GenAI Track at the Master School Institute of Technology
• Development of a full-stack AI application (React + Python/FastAPI) for automated supplier product import with intelligent column and category classification (4-layer hierarchical) including human-in-the-loop validation

• Analysis and remediation of security vulnerabilities in a risk assessment system for energy trading
• System analysis
• Threat modeling
• Decision-making on vulnerability mitigation strategies
• Implementation of vulnerability detection mechanisms
• Security scans
• DevSecOps practices
• Technical environment: Visual Studio Code, JetBrains Suite, MS Threat Modeling Tool, DevSecOps, Git, AWS, DynamoDB, SQL Server, Endur, Snowflake, Orca
• Languages: C#, JavaScript, TypeScript, Python, PowerShell, Bash, Terraform, SQL

• Analysis
• Consulting
• Software design
• Development
• Automation
• Testing
• Deployment
• Architecture, development and deployment of various proof-of-concept applications around the integration of current AI interfaces including conversational, realtime voice, images and videos
• Developed best practices for working with agentic systems and AI in practice
• Created code templates