Master Thesis: AI-generated Golden Paths for Platform Engineering

Join our Team

About this opportunity

R&D production systems, CI/CD pipelines, and service-to-service integrations often rely on long-lived credentials, which can be exposed, misused, or remain valid beyond their intended purpose. Modern public cloud architectures address this with workload identity federation, giving workloads short-lived credentials and shifting the focus from rotating secrets to governing trust relationships.

This thesis explores how these principles can be extended to R&D production environments and combined with Just-in-Time (JIT) and Just-Enough Access (JEA) to reduce persistent credentials and standing privileges.

What you will do

You will investigate and evaluate an architecture for continuous, risk-adaptive workload authorization:

Workload Identity → Federation → JIT/JEA Authorization → Continuous Risk Evaluation → Adaptive Enforcement

Your work will focus on how federation, JIT/JEA authorization, and AI-assisted risk evaluation can reduce reliance on persistent credentials while enabling adaptive control of production access. You will also examine which federation patterns transfer to R&D, how JIT and JEA apply to non-human identities, which signals should trigger reassessment of trust, and how far AI-assisted analysis can support automated restriction or revocation without losing explainability, predictability, or reliability.

The expected outcome is a reference architecture and governance model for continuous workload trust, supported by an empirical evaluation of its security and operational characteristics.

The skills you bring:

• You are pursuing a Master’s degree in Computer Science, Information Security, Software Engineering, Data Science, or a related field.
• You have solid programming skills in Python, Java, or a similar language.
• You are interested in cybersecurity, secure software engineering, AI/LLMs, and workflow automation.
• Familiarity with Git/GitLab, CI/CD, security assessments, or n8n is an advantage.
• You work systematically, independently and communicate clearly in English.
• This thesis is suitable for 1-2 students, preferably 2.