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About this opportunity
This thesis work proposes to develop and test a ‘Multi-agent ecosystem for feature-centric traceability and internal + external releases quality assurance and quality gating in for a cross-functional teams-oriented Organization supporting agile ways of development a complex ASIC IP.
What you will do
The proposed eco-system will ingest requirement specifications and connect them with Jira work items movement, RTL revisions for optimization or feature-changes, Documentation updates e.g. DS, VS, reference-model implementations, verification evidence, FPGA builds and release baselines.
Specialized agents are proposed to operate under clearly defined roles, while a coordinating agent will construct an auditable artifact graph, perform change-impact analysis and generate explainable quality-marker reports.
The research will combine LLM-based semantic reasoning with deterministic version, dependency and quality-gate rules. The prototype will be evaluated using traceability accuracy, warning precision, evidence completeness, unsupported-claim rate and practitioner assessment.
The expected contribution is a technically rigorous approach for improving XFT autonomy while preserving system-level consistency, release transparency and engineering accountability.
The skills you bring
Curious mind
Knowledge in Computer Science, Electrical Engineering, or a related field.
Experience in at least one programming language (Python not mandatory).
Eagerness to learn and explore new concepts.
Bonus: experience in machine learning.
Job description provided by Ericsson.
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