Master Thesis Knowledge Management for Agentic AI (f/m/x)

Our team at the BMW Group researches how enterprise knowledge can be transformed into a governed, machine-actionable foundation for autonomous AI agents. As part of our Enterprise Context Layer initiative, we explore knowledge graphs, retrieval architectures, and agentic AI concepts to build a living enterprise world model.

What awaits you?

• You support the analysis of how established knowledge management practices, such as versioning and provenance tracking, can be adapted for agent-consumed context.
• Furthermore, you help evaluate architectures such as knowledge graphs, vector and hybrid retrieval systems, and MCP-based context delivery for enterprise agents.
• In addition, you contribute to research on scalable knowledge storage, auditability, and low-latency context injection into agent runtimes.
• Moreover, you assist in exploring the organizational and architectural changes needed to transform static documentation into a living, auditable world model for AI agents.

What should you bring along?

• Studies in Computer Science, Information Systems, or a related discipline
• Strong interest in knowledge graphs and semantic data structures
• Strong interest in LLM and agent architectures
• Strong interest in enterprise knowledge and data management
• Python programming skills are a plus
• Experience with Semantic Web technologies is a plus
• Very good English skills

Would you like to help shape the foundations of trustworthy enterprise AI agents? Then Apply now!

What do we offer?

• Comprehensive mentoring & onboarding.
• Personal & professional development.
• Flexible working hours.
• Mobile work.
• Attractive & fair compensation.
• Apartments for students (subject to availability & only at the Munich location).
• And much more, see bmw.jobs/waswirbieten

Start date: earliest start 07.09.2026

Duration: 6 months

Working hours: Full-time

You can find helpful tips on your application and the application process here.

At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants. Learn more here.