Shubham Shetty
Software engineer and CS graduate student building databases, distributed systems, and AI-powered tools.
Amherst, MA · [email protected]
Projects
- KodaDB
A persistent relational database built from scratch in C++17.
Database internals with a live SQL shell
- CacheBlendPlus
Faster LLM serving for RAG by extending CacheBlend with semantic-aware KV cache reuse.
Semantic KV cache reuse for faster RAG inference
- TaskBell
A free, local-first tool that pings you on your phone when an AI coding agent finishes, errors, or needs an answer.
Two-way notifications for AI coding agents
- Wanderwall
An NFC-powered travel gallery that turns a fridge magnet tap into a spinning globe flight and a photo gallery.
A globe that flies to your next trip
- FairSplit
An AI receipt splitter that turns messy grocery and delivery receipts into a fair settlement.
AI-parsed receipts, split fairly
- FloatNote
A privacy-first Chrome extension for highlighting web pages and jotting floating sticky notes.
Floating notes for the whole web
Experience
Incoming Software Engineer Intern · AWS Redshift
Sep 2026 — Nov 2026
Palo Alto, CA
- Working on query and planning optimization inside the C++ and Python codebase that powers Redshift's query planner.
Forward Deployed Engineer Intern · C3.ai
Jun 2026 — Aug 2026
Redwood City, CA
- Engineering a Premise Awareness feature for a San Mateo law enforcement platform, fusing data across 16 police departments so first responders see hazards, photos, and prior incidents before arriving on scene.
Software Engineer II · JPMorgan Chase
Jan 2024 — Jul 2025
Mumbai, India
- Developed and deployed a GPT-4 powered natural language to SQL interface that let non-technical users query complex data lake schemas, cutting analytics turnaround time by 70%.
- Spearheaded ETL pipelines on AWS using PySpark and Pandas, processing data from 85+ sources and over 20GB daily, saving $150K+ a year by decommissioning legacy workflows.
- Engineered a reusable data ingestion framework supporting multiple sources and formats on AWS Lambda, Glue, and S3, cutting onboarding time for new data sources by 80%.
- Architected the backend using Spring Boot with Aurora PostgreSQL on AWS ECS, building REST APIs for 10,000+ production users and optimizing database queries for performance.
- Engineered a blue-green deployment strategy for ECS services with Terraform and Spinnaker, enabling zero-downtime deploys and rollback for critical production workloads.
- Built a user-facing dashboard with Java Spring Boot and ReactJS on AWS ECS, using AWS ElastiCache for caching to support 1,000+ active users.
Software Engineer I · JPMorgan Chase
Aug 2022 — Dec 2023
Mumbai, India
- Promoted to Software Engineer II in 18 months, in the top 3% of new hires globally, for high impact on critical data lake initiatives.
- Built a data lineage tracking solution for the data lake using AWS Neptune, improving data quality and observability and cutting compliance audit time by 40%.
- Authored a technical primer on using Liquibase for Redshift that drew over 700 unique visitors in 3 months and improved team knowledge.
About
I'm a software engineer and graduate student in Computer Science at UMass Amherst, focused on database systems and systems for deep learning. I spent close to three years at JPMorgan Chase building backend services, data pipelines, and a natural language to SQL interface used across the firm's data lake. I built KodaDB, a relational database engine written from scratch in C++17, and this site runs on it. I'm interning at C3.ai now and join AWS Redshift's query planning team this fall.
- Certifications
- AWS Solutions Architect
- Databases
- PostgreSQL, MySQL, Firebase, Firestore
- Frameworks
- PyTorch, PySpark, Spring Boot, Flask, Django, Pandas, LangChain, LangGraph, Node.js, React, Next.js
- Infrastructure
- Linux, AWS, Git, Docker, Terraform, Jenkins, CI/CD, Spinnaker
- Languages
- Python, C++, Java, JavaScript, TypeScript, Go, Bash, SQL