IBM Consulting

• Serve as technical lead and primary client contact across three concurrent production-grade agentic AI development teams, coordinating 12 engineers across implementation, DevOps, and CI/CD automation.
• Define cross-project engineering standards, application monitoring strategy, and CI/CD templates — ensuring consistent delivery quality and operational visibility for enterprise client stakeholders.
• Drive architecture decisions and technical escalations, translating complex AI system behavior into clear narratives for client engineering leadership.

IBM Consulting

• Technical lead and architect of IBM Consulting's enterprise RAG accelerator — delivered technical workshops, architecture proposals, and proof-of-concept engagements that directly enabled 10 major client projects.
• Designed and deployed a secure public-facing RAG chatbot, eliminating 95% of hard-coded intents and demonstrating efficiency gains to C-suite stakeholders at a leading enterprise client.
• Led end-to-end delivery of a GenAI-powered patent and invention analysis solution for a global automotive OEM — from client architecture workshops through production launch, achieving >70% daily adoption among IP experts.
• Delivered customer-facing GenAI knowledge-sharing sessions covering model evaluation, semantic & hybrid search, reranking, and LLM concepts — enabling non-technical client stakeholders to evaluate and adopt AI solutions with confidence.
• Ran prompt engineering workshops with non-technical customer stakeholders and internal DevOps & Python best-practices enabling sessions for engineering teams.
• Architected and executed migration of enterprise data platform from Azure SQL Database to Snowflake, enhancing 10+ production data pipelines and presenting technical recommendations to client data leadership.

RELEX Solutions

• Built and maintained initial data platform infrastructure for streaming and batch processing — including networking, service integrations, and GitLab CI/CD pipelines using Terraform.
• Set up, configured, stress-tested, and maintained Apache Kafka clusters across US and EU regions; implemented platform monitoring, logging, and alerting from the ground up.

German Cancer Research Center

• Researched and implemented federated learning for large-scale 3D MRI segmentation.
• Published findings at MICCAI DeCaF Workshop (2022) and contributed significantly to the open-source Kaapana imaging platform.

Towards Real-World Federated Learning in Medical Image Analysis Using Kaapana

MICCAI DeCaF Workshop

Kades K.; Scherer J.; Zenk M.; Kempf M.; Maier-Hein K. · Sep. 2022