GitHub Experts in Dusseldorf

• Training the AI models, evaluating images and texts for UI/UX, turning the provided data into insights via OpenAI Feather as part of the machine learning workflow

Technologies: OpenAI Feather

Project: Concept and implementation of an AI product for four business use cases

Project management of an AI project at a leading provider of large-scale catering and food services, where a production-ready AI product for four use cases was implemented together with an external development partner: automated briefings from CRM and document data, voice-based capture and structuring of reports, detection and merging of duplicates in master data, and data-based market analysis. A central focus was a privacy-compliant architecture that passed the internal IT security review and enabled productive use.

• Translating business requirements into clearly defined AI use cases with a clear product scope and clear value proposition
• Selecting and evaluating models and architecture options for text extraction, speech-to-text and context enrichment from business systems, including LLM integration, function calling and retrieval
• Designing and enforcing an architecture with European hosting, data minimization and masking of personal data as a prerequisite for approval
• Managing the interfaces between business, IT, IT security and the external development partner under restrictive data access conditions
• Coordinating with CIO and executive management on data access, risk assessment and approval decisions
• Preparing the transition into productive use

Seqnaut and Sycosm (WIP) – Embedded Audio DSP & Synthesis Platform

• Embedded audio DSP framework — synthesizers, effects, drum machines; modular audio graph
• Sequencing: PianoRoll, StepGrid, MasterClock; 8-voice polyphonic synth; CLI + OSC
• Transient Detector — dual-envelope adaptive threshold, guitar attack detection
• Hardware: Teensy 4.1, custom AFE design tapping BOSS GX-100; MIDI FX integration

Label: C++23, C, Python, CMake, FreeRTOS, Teensy 4.1 (ARM Cortex-M7), Teensy Audio (Stoffregen), DaisySP, I2S/SAI, OSC, MIDI

• 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

• 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.

• Full focus on AI-augmented web development
• Building and running three proprietary AI-native SaaS products (BrainButler, PageUpgrade, termin365)
• Developing a self-hosted business stack for digital sovereignty
• Daily workflow with Claude as engineering partner and Anthropic/OpenAI APIs for product features
• Using RAG systems with custom vector databases and prompt engineering for complex multi-step pipelines
• Tech stack: Python/FastAPI (backend), React/TypeScript (frontend), WordPress plugin architectures (PHP), multi-tenant systems with per-user encryption

• Built and launched the AI-powered “E-Invoice Corrector,” an intelligent system for validating and correcting invoices, using Python, FastAPI, and machine learning. The system is now live at Fintom8.
• Converted the Corrector into a fully functional API, published with Swagger documentation for easy access and integration by internal and external consumers.
• Designed, experimented with, and optimized advanced LLM prompts and meta-prompting strategies to improve automated reasoning, error correction, and decision-making in agent workflows.
• Wrapped and integrated existing APIs within the Google Agent Development Kit (ADK) framework to enhance automation capabilities and conversational AI workflows.
• Implemented comprehensive unit testing using pytest and unittest, and employed breakpoint debugging (VS Code, pdb) to ensure code reliability, maintainability, and smooth runtime execution.
• Utilized Pydantic and Tabulate for structured data validation, API schema management, and clear tabular data representation in testing and debugging workflows.
• Pursuing the Google Cloud Professional Certificate.

• Design and implementation of a system to control the entire process for new, removal, and exchange operations of electricity meters by external service providers for a utility company

• Automated retrieval of orders and available devices via defined interfaces (e.g. from SAP)

• Orchestration of process steps (assigning meters, processing meter data, sending updated information back to the source system) using a Spring Boot backend

• Provision of a React-based web client for operational tracking and control of orders, e.g. to continue failed process steps or resend notifications

• Analysis of the possibility of extracting market location data into a separate microservice within an overarching web portal
• Developing a more user-friendly target process based on the current process in coordination with the users
• Coordinating the related architecture concept with architects and developers
• Aligning the related epics and user stories with the relevant departments
• Backlog prioritization and project planning (incl. effort estimation)
• Testing and accepting the implemented user stories
• Technologies/Tools used: MS Office, Jira, Mural, Kotlin, React, GitHub, MS Azure, SQL, Postman, XML, JSON, Kafka, Balsamiq, BPMN

• Led the development of robust, scalable, and high-performance micro-services architecture.
• Migrated legacy monolith systems to Spring Boot with RESTful APIs.
• Designed, implemented, deployed, tested, and optimized scalable backend systems ensuring high availability and performance.
• Maintained and deployed Dockerized applications on Kubernetes integrated into CI/CD pipelines.
• Collaborated with cross-functional teams, including frontend developers, product managers, and designers, to translate business requirements into scalable and efficient backend solutions.
• Mentored team members and contributed meaningful code reviews.

• Forecasting Cost Tool (PCCT) imports data via SSIS from CSV files and processes modules for administrator, user management, train operations, and fleet operations.
• Conducted requirement analysis and effort estimation.
• Designed database and developed web pages.
• Tested the application.

• Setting up and enhancing an international subscription management system

• Migrating and decommissioning a Hybris-SAP system and integrating Zuora

• Implementing numerous interfaces to various systems (external and internal)

• Setting up and improving monitoring with Grafana, Prometheus, and Databricks

• Introducing logging with Loki

• Implementing business requirements using jQuery, Thymeleaf, Spring Boot, Java, Go, and Python

• Adjusting and extending the GitLab CI pipelines

• Setting up and extending infrastructure as code with Terraform and ArgoCD on AWS

• Setting up and running E2E and performance tests

• Expanding the Databricks business intelligence solution to provide various KPIs

• Responsibilities: Architecture, DevOps, development, unit tests, coaching employees and apprentices, E2E, smoke, and integration tests, agile methods consulting (Kanban, Scrum)

• Technologies and methods: Java, Go, Kotlin, Node.js, Spring Boot, SOAP/REST, Quarkus, Thymeleaf, Vaadin, Slack, Jira, Confluence, IntelliJ, GitLab, SQS, Kafka, AWS, Kubernetes, Terraform, Maven, Gradle, GitLab CI, Databricks

• Gather and analyze requirements in close collaboration with business units to develop data-driven solutions and scalable PowerBI reporting infrastructures.
• Perform detailed debugging and optimize existing semantic and data models to ensure a robust data architecture, high data quality, and improved PowerBI reporting.
• Design and implement scalable ETL processes for data preparation and integration.
• Create a wiki for table and view descriptions as well as PowerBI PowerQuery and KPI documentation to ensure a consistent understanding of data structures and metrics.

• Implemented communication between heating system modules via the SOME/IP interface in C++
• Developed additional software components in C++
• Executed unit tests and integration tests in the GitLab CI workflow
• Set up desktop publishing functionality
• Tools: C++, Python, Linux, Robot Framework