Master Thesis: AI-generated Golden Paths for Platform Engineering
Ericsson ABNy
Sammanfattning
This thesis opportunity focuses on enhancing R&D production environments through the exploration of workload identity federation, Just-in-Time (JIT), and Just-Enough Access (JEA) to minimize persistent credentials. The role involves investigating an architecture for continuous, risk-adaptive workload authorization, with an emphasis on AI-assisted risk evaluation. The position is based in Linköping, Sweden, and is suitable for 1-2 Master's students in relevant fields.Det här erbjuder vi
Opportunity to work on innovative solutions to complex problems.Collaboration with a diverse team of innovators.Encouragement of a diverse and inclusive work environment.
Ansök senast: Öppet tillsvidare
Publicerad: 2026-10-31
Beskrivning
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:
Why join Ericsson?At Ericsson, you'll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what's possible. To build solutions never seen before to some of the world's toughest problems. You'll be challenged, but you won't be alone. You'll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Linköping
Req ID: 792245
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.
Why join Ericsson?At Ericsson, you'll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what's possible. To build solutions never seen before to some of the world's toughest problems. You'll be challenged, but you won't be alone. You'll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Linköping
Req ID: 792245
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Master Thesis: AI-generated Golden Paths for Platform Engineering
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Ericsson AB
