Internship - Computer Science, AI, Software Engineering, or a related field

We are looking for an intern to improve engineering productivity across the software development lifecycle by combining agentic AI and practical automation.

You will work on real pain points the team experiences every day:

• Manually orchestrating different perspectives (product owner, architect, developer, QA) during story refinement
• Long feedback loops caused by full builds, expensive test runs, and change propagation across multiple repositories
• Recurring manual release verification steps that could be automated

The goal is not a demo or proof-of-concept. We want working solutions the team can actually adopt and continue using after your internship ends, with measurable impact on story quality, feedback speed, or release confidence.

You will have significant autonomy to shape the direction (agentic AI for refinement, release/build/test acceleration, or a combination of both), choose your tools and architecture, and validate your ideas with real users and real workflows.

Key Responsibilities

• Needs analysis — Map the current Jira workflow and release process. Identify where agentic AI or automation can deliver the highest practical value.
• Agent design & integration (primary track option) — Design a multi-agent system in which specialized agents (analyst, architect, developer, QA, etc.) collaborate to refine Jira stories, challenge scope, enrich acceptance criteria, surface risks, and provide implementation guidance. Integrate the pipeline with Jira so it can read stories, post enriched content, and assist during refinement and sprint planning.
• Release & validation acceleration (primary track option) — Analyze build and validation bottlenecks across repositories. Investigate incremental builds, change-impact analysis, selective test execution, dependency-aware pipelines, and smarter validation stages (pre-check → component → integration → full release). Design and implement tooling that reduces unnecessary work and manual change propagation.
• Test automation — Convert high-value repetitive manual test plans into reliable automated checks.
• Measurement & adoption — Define success metrics, measure before/after impact on real stories or release cycles, gather team feedback, document the solution, and help the team adopt what you build.

You are free to choose frameworks, languages, and architecture. What matters is that the result works, integrates cleanly, is maintainable, and is something the team wants to keep using.

Example Directions You Could Explore

• Multi-agent refinement of a raw Jira story into structured requirements, acceptance criteria, risk flags, and implementation hints
• Triggering only the builds and tests affected by a given change
• Automatically determining which repositories need follow-up validation after a change
• Reducing the number of manual pull requests required to propagate changes through the stack
• Automating recurring release verification steps that are currently done by hand
• Dashboards or reports that show release readiness and bottlenecks

Qualifications

• Eligible to work in Kortrijk, Belgium
• Available for a minimum of 6 months
• Student in Computer Science, AI, Software Engineering, or a related field
• Strong programming skills (Python or TypeScript preferred)
• Solid understanding of LLMs, prompt engineering, and multi-agent concepts or strong interest in developer productivity, CI/CD, and automation
• Comfortable working with APIs and integrating third-party tools
• Fluent English (spoken and written) is a must

Nice to have:

• Hands-on experience with AI agent frameworks (LangChain, LangGraph, AutoGen, CrewAI, or similar)
• Familiarity with Jira / Atlassian APIs
• Experience with test automation, CI systems, or release engineering
• Exposure to multi-repository development or C++
• Experience with software development workflows (agile, scrum, story refinement)