Experience
Where I've worked and what I've built.
BCG Platinion, SAP, Allianz, Fraunhofer, and TUM. What I've worked on and what I've learned along the way.
Intern — AI Research & Engineering
Technical University of Munich × SAP
Product owner and architecture lead for an orchestrator-free multi-agent system built as part of the TUM SAP Practical Course. Designed the full system architecture and led a team of 6 through research, implementation, and stakeholder presentations.
- Orchestrator-free agent swarm architecture with reputation-weighted bidding, append-only blackboard, and citation-based stigmergy for emergent consensus
- Agent topology and protocol design — contract structure, tool definitions, and interaction rules governing agent communication and task self-selection
- UI — visual canvas playground for configuring agent networks and simulating live swarm runs with step-by-step playback
- Product ownership — backlog management, sprint coordination, and technical presentations to SAP industry stakeholders
Working Student — AI & Data Analytics
BCG Platinion (Boston Consulting Group)
Contributing to AI strategy initiatives within the Energy practice. Co-designing stakeholder workshops on AI adoption. Delivering AI-powered solutions for enterprise clients.
- AI strategy for energy value chains — GenAI adoption, architecture design, feasibility
- Stakeholder workshops on AI impact, risks, and adoption strategies
- Technical architecture slides — GenAI system design, data pipelines, governance
Working Student — AI/ML
Allianz SE
Developed GenAI applications for insurance operations. Designed agentic workflows with cost-optimized model selection. Drove adoption through stakeholder workshops.
- GenAI applications — customer communication analysis, medical report insights, insurance evaluations
- Agentic workflow design with cost-benefit analysis across models and cloud providers
- Prompt engineering framework presented in stakeholder workshops
- CI/CD pipelines (Jenkins) for promoting agentic workflows to production
Intern — Generative AI
Fraunhofer Society
Built a private RAG pipeline for institutional knowledge management. Led improvements in data ingestion, retrieval quality, and AI security.
- Private RAG pipeline using institutional public data
- Data ingestion optimization and retrieval quality improvements
- Guardrail design — anti-hallucination, prompt attack resistance
- Prompt engineering for reliable, secure knowledge management
Research Author — LLMs for Science
Published in JSEP (Journal of Software: Evolution and Process)
Co-authored a peer-reviewed paper on the use of LLMs in research and data analysis. The work has been cited over 170 times (55+ on Scopus), contributing to the academic discourse on AI adoption.
- Peer-reviewed publication on LLM usage for code generation and data analysis
- 170+ citations, 55+ on Scopus — serving as a foundation for AI-driven research training
- Contributed to the academic discourse on responsible AI adoption in scientific workflows
Skill map
Capability Graph
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Showing 13 of 13 nodes.
Technical Skills
Search across the full skill set, then scan only the categories that match.
AI & Machine Learning
coreFrontend Engineering
coreBackend Engineering
coreCloud & DevOps
workingArchitecture & Product
workingStrategy & Delivery
workingResearch & Foundations
workingEcosystem & Tooling
workingLanguages
- English (Fluent)
- German (Fluent)
- French (Native)
- Arabic (Native)
- Spanish (Basic)
Sectors
- Enterprise AI / Consulting
- Insurance & Financial Services
- Energy & Utilities
- Research & Higher Education
Ways of Working
- Agile / Scrum delivery
- Stakeholder workshop facilitation
- Feasibility & cost-benefit analysis
- Architecture & solution design