[2027] Streamlit QA Platform Engineering Intern (Python, DRC, Dashboards)

About the Role

We’re seeking Computer Science interns to build a production-style QA platform delivered as a Streamlit app. The app will trigger and monitor DRC runs, track cycle time (days to completion), iteration history, and rule stability, and include a simple in-app chatbot for common engineer FAQs.

What You Will Do

• Build a multipage Streamlit app with navigation, session state, and role-based views.
• Create pages for creating and launching QA runs, monitoring progress, and reviewing results.
• Develop KPI dashboards for cycle time (days), pass/fail rates, iteration counts, and stability trends.
• Implement robust error handling, caching, and support for long-running/background tasks.
• Integrate with a DRC tool (e.g., KLayout or Calibre if available) to execute checks from the app.
• Parse and normalize DRC reports; link violations to rule IDs, run IDs, and timestamps.
• Implement a rule registry with metadata (ID, description, deck reference, owners, severity, status).
• Track rule updates and QA history; compute stability signals (no-change windows, regression flags).
• Design schemas for runs, results, rules, and artifacts (PostgreSQL or SQLite).
• Persist logs, reports, and attachments with traceable metadata and audit trails.
• Add a simple chatbot to answer FAQs (how to run QA, rule descriptions, common errors) using lightweight retrieval over internal documentation.