Erstellt am 19. Juni 2026
Thesis - Automated Text Interpretation for Development Requirements (all genders welcome)
Audi
Neckarsulm, Baden-Württemberg 74172, Germany
Vollzeit
Reference: 308967610
Work Environment
The Powertrain Development department at AUDI AG shapes the future of efficient and innovative drive systems. Our focus is on clear requirements engineering to optimize development processes and ensure quality. You will contribute to the development of cutting-edge, LLM-based knowledge retrieval systems by building intelligent interfaces between enterprise applications and modern AI infrastructure.
Job Purpose/Role
• Develop an end-to-end approach for clear development requirements
• Integrate heterogeneous data sources and types of data to extract and interpret relevant information for technical and functional requirements to provide knowledge for AI systems
• Generate a knowledge graph based on identified key information and create a requirements architecture
• Definition of embedding pipelines, indexing strategies, and optimization of data retrieval to support LLM-based knowledge access
• Documentation of integration processes and technical workflows
Key Requirements/Skills/Experience
• Enrolled Master's student in IT-related fields such as Business Informatics, Business Intelligence, Data Science, Computer Science, or similar
• Programming experience e.g. in Python, familiarity with data analysis libraries (e.g., pandas, NumPy)
• Experience in RAG, knowledge graphs, semantics and text interpretation, LLM-development
• Analytical and structured thinking with enthusiasm for understanding large data sets
• Possible approaches: MCP servers, vector databases, and other semantic interfaces
• Close collaboration with AI engineers, data architects, and system owners to ensure scalable, secure, and reusable connector templatesYou will agree on your internship period in close alignment with the department.
The Powertrain Development department at AUDI AG shapes the future of efficient and innovative drive systems. Our focus is on clear requirements engineering to optimize development processes and ensure quality. You will contribute to the development of cutting-edge, LLM-based knowledge retrieval systems by building intelligent interfaces between enterprise applications and modern AI infrastructure.
Job Purpose/Role
• Develop an end-to-end approach for clear development requirements
• Integrate heterogeneous data sources and types of data to extract and interpret relevant information for technical and functional requirements to provide knowledge for AI systems
• Generate a knowledge graph based on identified key information and create a requirements architecture
• Definition of embedding pipelines, indexing strategies, and optimization of data retrieval to support LLM-based knowledge access
• Documentation of integration processes and technical workflows
Key Requirements/Skills/Experience
• Enrolled Master's student in IT-related fields such as Business Informatics, Business Intelligence, Data Science, Computer Science, or similar
• Programming experience e.g. in Python, familiarity with data analysis libraries (e.g., pandas, NumPy)
• Experience in RAG, knowledge graphs, semantics and text interpretation, LLM-development
• Analytical and structured thinking with enthusiasm for understanding large data sets
• Possible approaches: MCP servers, vector databases, and other semantic interfaces
• Close collaboration with AI engineers, data architects, and system owners to ensure scalable, secure, and reusable connector templatesYou will agree on your internship period in close alignment with the department.
