Vighnarth Nile

I’m a Computer Engineering graduate and AI/ML Engineer who builds end-to-end AI applications—from RAG pipelines and multi-agent systems to full-stack delivery. I’m especially focused on turning prototypes into scalable, production-grade solutions using Python and modern APIs.

In my AI/ML Engineering Internship, I architected a full-stack RAG-based conversational assistant to reduce manual HR onboarding latency. I improved context-retrieval accuracy with multi-agent orchestration using ChromaDB and SQLite, while managing user states, policy retrieval, and automated email generation.

As a Data Analyst Intern, I eliminated manual tracking overhead by developing SQL-driven automation for real-time inventory management and scrap supply-demand reconciliation. I also accelerated cross-team access by building optimized query and reporting pipelines over large enterprise datasets.

Right now, I’m leading projects like a Smart City Dashboard multi-agent urban monitoring system (LangGraph, FastAPI, ArcGIS API, PostgreSQL) and a LiveKit-based AI Voice Interview Agent with RAG persona generation and low-latency speech workflows. My work includes an IEEE publication on real-time skill gap analysis and adaptive career guidance, plus AWS Cloud Foundations certification.