evaluate how test automation could be combined with agentic AI to identify bottlenecks and facilitate workflows for test-case generation, refinement, automation preparation, and its review.
Automate test case generation
Increase the efficiency of test case automation
Implement new workflows aimed at increasing software quality
Map the current testing and automation workflow and pinpoint bottlenecks suitable for agentic support.
Evaluate agentic workflows for test-case generation, improvement, automation planning, and review.
Explore agent setups, tool integrations, and MCP/API-based workflows.
Compare approaches before recommending a tool, architecture, or implementation direction.

Familiarity with software testing, test-case design, and test automation concepts.
Scripting/programming knowledge, e.g. Python or similar.
Ability to navigate APIs, MCP-based integrations, system integrations, and structured test data.
Awareness of agent harnesses, tool-using agents, and current agentic development patterns.
Previous hands-on experimentation with agent-based tools, automation agents, or similar AI-assisted workflows.
Relevant master-level education in Computer Science, Software Engineering, Data Science and AI, Machine Learning, or Master of Science in Engineering (Civilingenjör) with a software, AI, automation or data-oriented specialisation.

Master Thesis Worker – Test Automation

Key skills