Bio
Passionate Software Engineer with deep expertise in Data Structures, Algorithms, and Object-Oriented Design. I design scalable backend systems, secure microservices, and high-performance REST APIs for distributed environments. Specialized in integrating production-grade AI/ML solutions into cloud-native applications.
Experience
Jan 2026 — Present
Software Engineer — AI/ML, BizInsights, Fremont, CA
Leading BizInsights' AI initiative as the sole engineer building AI into the product. Built a chatbot using LangChain that lets users query databases with plain language instead of SQL. Also designed the backend systems to run ML models efficiently and handle heavy database traffic without slowdowns.
Jul 2025 — Dec 2025
Research Intern, Binghamton University, NY
Worked with
Prof. Sujoy Sikdar to build datasets of interview question-answer pairs. Scraped and cleaned data from various sources, performed exploratory analysis, and prepared datasets for NLP research on conversational patterns.
Jul 2024 — May 2025
Software Engineer, StarQuest Technologies, Germantown, MD
Rewrote critical Django APIs to run asynchronously, dramatically improving response times and fixing persistent N+1 query issues. Added Redis caching and PgBouncer pooling to reduce database contention and keep traffic smooth on limited servers.
Sep 2022 — Apr 2023
Undergraduate Researcher, IIIT Kottayam, India
Worked with
Prof. Koppala Guravaiah to study performance problems in SDN data planes and built a smarter firewall using a Cuckoo filter, which cut errors and used less memory while allowing constant-time deletions.
Jun 2022 — Aug 2022
Machine Learning Research Intern, IIIT Kottayam, India
Worked with
Prof. Victer Paul to build a system that cleans up noisy scanned documents using AI, then scored different methods by measuring how well OCR tools and table parsers handled the results.
Jun 2022 — Jul 2022
Amazon Machine Learning Summer School, India
Spent a summer with Amazon scientists and engineers, learning firsthand how Amazon builds and operates ML systems at massive scale, covering production pipelines, huge model training jobs, and the real challenges of deploying NLP and deep‑learning services.
Built with just two static files (HTML, CSS). No frameworks, no build step. Keep it simple, as said in this manifesto (⚠️ Strong language warning).