GitHub Experts in Dresden

BAFA consulting and project support for the introduction of AI solutions and AI agents.

• Analysis of existing business and customer service processes and identification of automation potential
• Design of AI-supported processes and agents for communication, support, and internal operations
• Gathering and structuring requirements with the company’s contacts
• Planning implementation and coordinating between the client, consulting, and development teams
• Consulting on the integration of AI into existing workflows and systems
• Development of use cases and prioritization based on value and implementation effort
• Support with testing, adjustments, and the rollout of solutions
• Consulting on data protection, process design, and the use of AI within the company

Methods/Technologies: AI agents, on-premises LLM, RAG, prompt engineering, process automation, API integrations, n8n, project management.

• Development of backend systems with ASP.NET and MS SQL, plus client integration via AngularJS.
• Responsibility for the architecture and implementation of cross-platform apps for iOS, Android, and Windows with Xamarin native & Xamarin.Forms.
• External Xamarin consultant for business partners.

• Developed a comprehensive business concept for a medical fall detection device based on a patented process registered in Germany
• Identified and collected use cases for medical device deployment in residential buildings and healthcare provider facilities
• Expanded the product scope to industry standards such as HL7/FHIR and designed a product based on modern communication protocols for IIoT
• Supported offshoring activities, defined SLA and scope-of-work documents for development teams after selecting various vendors
• Identified and selected hardware components (Terrabee, E-Con Systems) for LIDAR/TDOA functions
• Defined integrated AI features and LLM models for patient fall detection as well as AI-based audio triggers
• Oversaw the implementation of algorithms for object detection, fall detection, and false alarm identification

• Further development of framework components and services in the Enterprise Banking Control Platform (EGP Framework), a set of cross-cutting libraries and services for all bounded context scopes of the platform.
• Migration from Java 17 to Java 21 and from Spring Boot 3.2 to 3.4 in about 80 library and service repositories (updating Maven POMs, Dockerfiles, Jenkins pipelines, source code migration, test updates).
• Writing unit and integration tests with JUnit and JGiven.
• Performing and analyzing performance measurements with Dynatrace.
• Enhancing multi-stage CI/CD pipelines (unit tests, security analyses, Docker builds, Harbor deployments, ...).
• Tech stack used: Java (90%), Python (10%), Spring Boot, JPA/Hibernate, JGiven, OpenAPI, Camunda 7, Podman, OpenShift/Kubernetes, Oracle DB, SonarQube, Dynatrace, Jenkins, Harbor, Bitbucket, Jira, Confluence.

• Complete redevelopment of a time and work tracking software for student support and people with disabilities.
• Responsible for the fundamental restructuring of the code using Angular 19 (frontend) and Next.js (backend) on a TypeScript basis.
• Implemented as a monorepo with NX workspace.
• Set up AWS infrastructure and built a GitHub CI/CD pipeline for automated deployments.

• Implemented accessibility audit recommendations for the ICE onboard portal to improve usability for screen reader and keyboard users
• Migrated end-to-end tests from Cypress to Playwright
• Refactored components to meet accessibility standards
• Introduced Prettier for consistent code formatting

• Developed an adapter from the central foreigner register to an internal application
• REST, JSON, OpenAPI, Spring Boot, Vue, Java, Maven, XAusländer
• Jira/Confluence/GitHub, Scrum+Kanban

• Technical and professional management of software and ML development; largely independent programming and guidance of the team and external project partners
• Design, creation, and preparation of training and test datasets from experimental image data and simulations
• Selection, implementation, training, validation, and testing of neural networks for image-based reconstruction and transformation
• Systematic evaluation, comparison, and optimization of various model architectures (convolutional neural networks, generative adversarial networks, autoencoders, transformers)
• Design and implementation of explainable AI analyses to assess model interpretability and robustness (feature map analysis, augmentation studies, guided backpropagation)
• Presentation of the developed methods and results at project meetings and international conferences