Software Engineer crafting data pipelines, AI systems, and enterprise solutions. 2.5+ years at Deloitte, Elevance Health & Microsoft — turning complex problems into clean, scalable code.
I'm a Software Engineer at the intersection of data engineering, artificial intelligence, and backend systems. I transform messy business problems into clean, production-grade software — from high-throughput ETL pipelines to GenAI-powered RAG systems.
At Deloitte, I engineer analytics pipelines for large-scale audit programs. Before that, at Carelon Global Solutions (Elevance Health), I architected database solutions handling 50K+ daily healthcare transactions with 99.9% uptime. I started as an AI Intern at Microsoft, building ML models for predictive analytics.
Production-grade Python apps, REST APIs, OOD, and full SDLC — built for performance and scale.
RAG pipelines, prompt engineering, ML models, and LangChain workflows for enterprise intelligence.
ETL pipelines, AWS, BigQuery/Snowflake, Docker & Kubernetes — data at scale.
From healthcare systems to enterprise audits — shipping impactful software.
Built a RAG system for semantic enterprise search. Implemented FAISS vector embeddings and prompt engineering workflows for automated insight extraction.
ML model predicting used car prices with 92% accuracy using regression. Built a Tkinter GUI for real-time price estimation.
Python app converting digital text to handwritten format with 30+ styles. Customizable writing patterns adopted by peer groups.
I'm interested in new opportunities, challenging problems, or a good conversation about software and AI.