Case Study / 003Software Systems · 2026

Faculty Operations Platform

NYU's Office of Faculty Affairs ran records, workflow routing, and approvals for 500+ faculty through manual, form-based processes.

A team-built Django REST Framework and PostgreSQL platform that moves faculty-affairs paperwork into structured workflows with approval tracking, scheduled automation, and document storage across AWS S3 and Azure Blob Storage. I worked on it as a Software Engineer from January to August 2026 alongside other engineers — this page covers my contributions, not the whole platform.

FIG. 09ASimplified workflow excerpt — one generic example path with a revision loop. Internal operational details (specific rules, thresholds, approval chains, form fields) are omitted; this illustrates the shape of coordinated workflow handling, not the platform's actual internal logic.

My contributions

Django REST Framework APIs and PostgreSQL-backed workflows supporting faculty operations.
Celery Beat scheduling for administrative workflows, including approval and escalation logic.
An Excel data importer, plus end-to-end integration tests for the workflow paths.
AI-powered document classification across AWS S3 and Azure Blob Storage.
A LangChain/FAISS RAG chatbot for natural-language search of faculty policy information.

From my work

20test cases validating the Excel importer I built

3pre-release defects surfaced by integration tests I wrote

~60% (est.)estimated reduction in manual record lookup time from AI document classification

FIG. 09BFunctional index of the platform's main Django apps, grouped by function for presentation — a team-built codebase; not a dependency graph or a map of individual ownership.

Stack

Django REST Framework / PostgreSQL / Celery Beat / LangChain / FAISS / AWS S3 / Azure Blob Storage