Work environment

The research is embedded within the Data & AI Products area at the DataLab Munich, an environment that develops and supports AI solutions in the enterprise context across all business units of the Volkswagen AG. The DataLab’s overarching focus includes Generative AI, classical machine learning, reinforcement learning, optimization, and robotics, providing a broad and stimulating research environment. The DataLab maintains long‑established, close collaborations with leading academic research groups, including Ludwig Maximilian University (LMU), the Technical University of Munich (TUM), the University of Vienna, as well as international institutions. In addition to industrial relevance, the value of principled, foundational research is explicitly recognized, and engagement with fundamental scientific questions beyond immediate product development is actively encouraged. You will research and advance agentic AI technologies as well as orchestration approaches for large language models in industrial and enterprise‑wide application environments. The focus is on developing scalable and robust AI systems that enable autonomous workflows and intelligent automation. In addition to conducting excellent research, the role contributes to Volkswagen’s agentic transformation by transferring research outcomes into real internal IT applications and AI products. The position combines scientific innovation with practical implementation in close collaboration with academic and industry partners. If you would like to actively shape the future of agentic AI, we look forward to receiving your application.

Possible Tasks within this Role

• Researching, designing, and implementing scalable agentic AI architectures and orchestration frameworks for large‑language‑model‑based systems
• Developing and prototyping autonomous agents and multi‑agent workflows, integrating LLMs with internal IT systems, tools, and enterprise data sources
• Contributing hands‑on to the development and enhancement of internal AI products, including implementing, testing, and evaluating agentic capabilities
• Shaping and supporting the company’s agentic transformation by identifying, designing, and implementing intelligent automation solutions for internal IT use cases
• Conducting scientific evaluation of developed approaches and publishing research findings in collaboration with academic and industry partners

The final doctoral topic is defined together with the professor. The prerequisite for the cooperation is the confirmation of supervision as well as a confirmed delimitation of topics by the professor of a university or research institution entitled to confer a doctorate.

Qualification requirements

• Good to very good university degree qualifying for doctoral studies in Computer Science, Computational Linguistics, Mathematics, Artificial Intelligence, or a related technical field
• Strong foundations in mathematics, machine learning, and software engineering, including experience in designing and implementing complex software systems as well as proven practical experience with generative AI and machine learning models, particularly large language models and related frameworks
• Solid programming skills in Python and experience with relevant AI/ML libraries and frameworks
• Experience with cloud platforms such as AWS and/or Microsoft Azure, including deployment and operation of AI services.
• Familiarity with version control systems (e.g., Git) and collaborative development workflows and tools
• English language level B2
• Strong analytical thinking, high level of initiative, and ability to work independently as well as collaboratively in interdisciplinary teams
• Excellent communication skills and ability to present complex technical concepts clearly

Keywords

Dissertation, GenAI, Agent Orchestration, AI Transformation, Conversational AI