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Thesis: AI-Assisted CI/CD Lifecycle: Development, Migration, and Maintenance Across Platforms

Knightec Group AB

Sammanfattning

This thesis position focuses on investigating the lifecycle of CI/CD pipelines across various platforms, emphasizing the role of artificial intelligence in enhancing implementation, migration, monitoring, and maintenance. Located in Sundsvall, the project will explore how AI can assist in understanding configurations, analyzing pipeline executions, and providing recommendations. The position is open to candidates graduating in June 2027 with a background in Computer Science or related fields, as
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Det här erbjuder vi

Opportunity to work on cutting-edge research in CI/CD and AI.Gain practical experience in software development and cloud technologies.Collaborate with industry professionals at Knightec Group.

De nordiska länderna

Ansök senast: Öppet tillsvidare
Publicerad: 2026-10-15

Beskrivning

High Level Description
CI/CD is an important part of modern software development, enabling organizations to automate the building, testing, and delivery of software. A wide range of cloud-based and self-hosted CI/CD platforms are available, each with different trade-offs in usability, flexibility, and operational requirements. At the same time, artificial intelligence (AI) is increasingly being used to assist developers and operations teams, while its application throughout the CI/CD lifecycle remains an emerging area of research.

This thesis will investigate the lifecycle of CI/CD pipelines across different platforms, from initial implementation and migration to monitoring and maintenance, with a focus on how AI can assist throughout the entire lifecycle.

Project Description
This thesis aims to evaluate and compare how AI can assist in implementing an end-to-end CI/CD pipeline on one platform, migrating it to one or more additional platforms, monitoring and finally maintenance.

AI assistance will be investigated throughout the pipeline lifecycle. During development and migration, AI could assist with understanding platform-specific configurations and translating between different CI/CD technologies. During operation, AI could be used to continuously analyse pipeline executions, logs, and configurations to identify potential issues and provide actionable recommendations.

Examples of relevant technologies include Jenkins, GitHub Actions, GitLab CI, Docker/Podman, Kubernetes, AWS, Azure, and AI/LLM APIs.


Who are we looking for?

  • Bachelor/Master of Science in Computer Science, Computer Engineering, or related fields.
  • Graduation in June 2027
  • Fluency in Swedish, both written and spoken
  • Fluency in English, both written and spoken


Purpose
In this thesis investigate the following areas:

1. CI/CD development and migration - Investigate the effort and challenges involved in implementing and migrating equivalent CI/CD pipelines across different platforms.

2. AI-assisted CI/CD lifecycle - Investigate how AI can assist developers throughout the lifecycle, including development, migration, monitoring, troubleshooting, and maintenance.

3. Pipeline health and maintenance - AI acts as an advisory tool that helps developers maintain healthy CI/CD pipelines by identifying potential issues, security concerns, highlighting likely causes of failures, and providing actionable recommendations.

4. Cross-platform AI integration comparison - Compare how well each platform integrates with AI tools, some may offer solutions that require minimal work to implement while some may require the creation of a custom interface between the AI and platform.
Limitations
The implementations are not intended to be production-ready systems, but rather proof-of-concept implementations suitable for experimentation and evaluation.
  • The application that the CI/CD pipelines are intended for is itself outside the primary scope of the study; its complexity and functionality should be sufficient to exercise the CI/CD pipelines but are not central to the evaluation.
  • AI assistance does not need to operate in real time. Batch analysis during normal operation and event-triggered analysis following pipeline failures are considered within scope.
  • The effectiveness of AI assistance may depend on the selected AI model, available pipeline data, logs, documentation, and other contextual information.
  • The study will focus on AI-assisted development, analysis and recommendations rather than fully autonomous modification or management of CI/CD pipelines.


    An Exciting Journey with Knightec Group
    Semcon and Knightec have joined forces as Knightec Group. Together, we are Northern Europe's leading strategic partner in product and digital service development. With a unique combination of cross-functional expertise and a holistic business understanding, we help our clients realize their strategies - from idea to complete solution.

Practical Information
This is a thesis position, located at our office in Sundsvall . Start date January or March 2027.

Please submit your application as soon as possible, but no later than 2026-11-30 . If you have any questions, you are welcome to contact johanna.edstrom@knightec.se . Note that due to GDPR, we only accept applications through our careers page.

Ansök till tjänsten

Thesis: AI-Assisted CI/CD Lifecycle: Development, Migration, and Maintenance Across Platforms

Denna arbetsplats har annonserats på Knightec Group SWE (former Semcon)-tjänsten den 2026-10-15 och publicerades av Knightec Group SWE (former Semcon).
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