Introduction

Join our Technology Systems Division in Stuttgart at the earliest possible date.

Tasks

• Supporting the structured capture of relevant project knowledge, workflows, constraints, design decisions, and best practices for use by AI tools
• Contributing to sustainable workflows that keep project-specific context accurate, complete, and up to date as the project evolves
• Assisting with the development and rollout of an AI-based Knowledge Interview tool, including AI-supported interviews with engineers and domain experts
• Preparing, structuring, and validating technical knowledge for effective use by AI assistants and agents
• Contributing to the development and evaluation of AI agents for engineering tasks such as hardware commissioning, test case creation, debugging, and the analysis of logs, traces, and system behavior
• Creating small tools, scripts, and automation workflows, preferably in Python
• Supporting experiments, proof-of-concepts, and evaluations of AI-based engineering workflows
• Documenting findings, limitations, and improvement opportunities in a clear and structured manner while collaborating closely with engineers, architects, and AI/tooling experts

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Qualifications

• You are currently enrolled in Computer Science, Electrical Engineering, Embedded Systems, Software Engineering, Data Science, Mechatronics, or a related technical field
• You have a strong interest in applying AI within large-scale embedded development projects and in understanding complex technical systems
• You bring analytical problem-solving skills, attention to detail, and a structured approach to identifying improvement opportunities
• You have good programming skills, preferably in Python, and ideally gained practical experience through university projects, internships, open-source contributions, or similar activities
• You have experience working with Linux and communicate openly and proactively within a team
• You are motivated to build reliable and robust processes and are comfortable asking questions, seeking support, and collaborating closely with others
• Experience with embedded systems, hardware-near software, testing or debugging, as well as knowledge of Docker, GitLab CI/CD, Kubernetes, Grafana, or similar tools, is advantageous
• An interest in AI agents, LLM-based tools, automation, developer productivity, knowledge management, or structured documentation is a plus

Contact and further information

You can expect very good payment, excellent terms and outstanding opportunities for growth and development.

We are looking forward to receive your application along with your resume, current transcript of academic records, and your current certificate of enrollment! The best way to apply is online using the reference number. If you have any questions, please feel free to contact your recruiting contact at any time.

You must be properly enrolled for the duration of your employment. You can work up to 20 hours per week during the lecture period. Mobile working is possible - but your main place of work is Stuttgart.

We place great importance on equal opportunities. We look forward to receiving your application regardless of gender, nationality, ethnic and social origin, religion, ideology, disability, age as well as sexual orientation and identity.

Reference number: 2351

Recruiting contact: Tanja Feßmann