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# Master Thesis - Development of Trustworthy Agentic AI iv)

- **Company:** Infineon
- **Location:** München, Germany
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Graph Database, Python (Programming Language), Tensorflow, Software Safety, Software Engineering, Explainable AI (XAI), Data Logging, Pytorch, LangChain, Uncertainty Quantification (UQ), Large Language Models, Software Security, Generative AI, Agentic-AI, Information Technology, Virtual Agents
- **Published:** October 1, 2026
- **Apply:** https://www.careerjet.de/jobad/def570627bdfc1baea83fe9799fc29831a

## About the Role

the final stage of your Master's studies in Computer Science, Artificial
Intelligence, Data Science, Software Engineering, Electrical Engineering, or a
related field Interests : You have a strong interest in Generative
AI, Large Language Models (LLMs), AI Agents, Trustworthy AI, AI Safety, or AI
Governance (Work)
experience : You have practical
experience with Python and modern AI/ML frameworks such as PyTorch, TensorFlow,
LangChain, LangGraph, or similar technologies Work
Style : You enjoy analytical
thinking, conducting independent research, and translating theoretical concepts
into practical implementations Personality : You bring curiosity, initiative, and a
structured approach to solving complex technical challenges in a
research-driven environment Skills : You ideally have knowledge of uncertainty
quantification, explainable AI, AI compliance, knowledge graphs, agent
architectures, or software security Language
Skills : You are fluent in
English; German language skills are considered a plus Please attach the following documents to your

## Description

you? Join us and make a difference. Whether you join as a student, intern, or
trainee, you'll be part of something real - real projects, real impact, and
real opportunities to grow. Are you in? Your role Key responsibilities in your new role Experience
research : You conduct a
comprehensive literature review on Agentic AI, AI safety, trustworthiness
frameworks, uncertainty quantification, AI governance, and autonomous agent
architectures Holistic
overview : You analyze current
architectural vulnerabilities, security risks, and limitations of existing
trustworthiness mechanisms in operational AI agent systems Shape
the future : You develop and
evaluate trustworthiness approaches for a baseline domain-specific AI agent and
assess their effectiveness in mitigating hallucinations and unsafe behavior Be
Creative : You prototype novel
trustworthiness mechanisms such as uncertainty-aware reasoning, semantic
traceability, neuro-symbolic guardrails, runtime validation, and zero-trust
execution logging Take
responsibility : You define and
evaluate quantitative metrics including hallucination detection accuracy,
auditability, compliance verification, uncertainty calibration, and system
performance overhead Keep
your colleagues informed :
You present research findings, recommendations, and future directions to AI and
technology teams Stay
up to date : You monitor emerging
developments in Trustworthy AI, AI Safety, Agentic AI, and AI Governance to
incorporate state-of-the-art approaches into your work Your profile Qualifications and skills to help you succeed Study
Field : You are currently in