A conversational assistant that recommends and runs GitLab pipelines and targeted test subsets based on source code changes, then reports results back to the user.
The agent understands available pipelines and test cases, inspects commits since the last execution, and recommends the most relevant pipeline and subset of test cases to run. Upon confirmation, it triggers the pipeline and streams/composes a final status summary when execution completes.
What You'll Work On
✔️ Inventory pipelines and test suites and expose them via a discoverable API ✔️ Parse commit diffs between runs to infer impacted areas ✔️ Generate run recommendations and explain the reasoning ✔️ Trigger pipelines and monitor status to completion ✔️ Post execution summary with key artifacts and links
What you will gain:
- Hands‑on Distributed Systems – Work with multi‑node orchestration and coordination
- AI/ML Infrastructure – Understand how production AI clusters are designed and operated
- Modern Python & Automation – Build production‑grade tools with Python, Docker, FastAPI
- DevOps & CI/CD – Use GitLab and automated pipelines for continuous integration and delivery
- Performance Analysis – Learn how networking performance is measured and improved
- Full‑stack Exposure – Build backend services and simple UIs for control and visualization
- Real‑world Impact – Ship features used by Keysight teams in day‑to‑day workflows
Skills required: Collective communication Libraries, RoCEv2, Python, Docker, FastAPI, SSH/SCP, distributed systems, AI/ML frameworks, automation, REST APIs, Linux, bash scripting
