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

April 2026 – July 2026 (Expected)·Munich, Germany·On-site

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)

November 2025 – Present·Munich, Germany·On-site

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

October 2024 – November 2025·Munich, Germany·Hybrid

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

March 2024 – July 2024·Munich, Germany·Hybrid

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)

October 2023 – January 2024·Munich, Germany·Research

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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AIFrontendBackendCloudArchitectureProductFoundations

Showing 13 of 13 nodes.

Technical Skills

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Showing 66 of 66 skills across 8 categories.

AI & Machine Learning

core
Large Language Models (GPT, Claude, Gemini, Bedrock Models)Agentic AI SystemsMulti-Agent ArchitectureRetrieval-Augmented Generation (RAG)Hybrid Search & RetrievalPrompt Engineering & OptimizationAgentic Workflows & OrchestrationFlow Engineering (Bedrock Flows)Document Intelligence & NLPMulti-Model OrchestrationHallucination MitigationAI Security & GuardrailsEvaluation & Reliability for LLM Systems

Frontend Engineering

core
TypeScript / JavaScriptNext.js / ReactTailwind CSSResponsive UI SystemsAccessibility (WCAG)Component Architecture (Radix UI)Data Visualization for AI Workflows

Backend Engineering

core
PythonJavaC++ / SystemCSQLFastAPIJava Spring BootNode.jsREST APIs & MicroservicesPostgreSQL / Vector DatabasesOCR & Document Processing Pipelines

Cloud & DevOps

working
AWS (Bedrock, SageMaker)Azure / Azure OpenAIVercel DeploymentDockerCI/CD (Jenkins)Environment Promotion WorkflowsProduction Readiness & MonitoringGit & GitHub

Architecture & Product

working
Solution ArchitectureSystem Design PatternsAgent Protocol DesignData Pipeline DesignProduct Ownership for AI ProjectsBacklog & Sprint PlanningStakeholder ManagementTechnical Decision Framing

Strategy & Delivery

working
AI Feasibility AssessmentCost-Benefit AnalysisModel / Provider Tradeoff AnalysisStakeholder Workshop FacilitationAgile / Scrum (Jira, Confluence)Technical DocumentationPresentation of AI Architectures to Business Teams

Research & Foundations

working
Trustworthy AI ResearchPrompt-Time Risk AnalysisEmpirical Evaluation DesignScientific Writing & PublicationComputer Architecture (FPU Design)Formal / Functional Foundations (OCaml)

Ecosystem & Tooling

working
LangChain / FlowiseClaude Agent SDKOpenAI APIsGemini APIsPrompt Frameworks for Enterprise Use CasesSemantic Search ConceptsKnowledge-Graph Style Skill Mapping

Languages

  • 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

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