2026 — Now
San Francisco, CA
San Francisco, CA
Backend engineer at Amazon Music who owns critical services end-to-end: architecture, reliability, performance, and developer tooling that accelerates teams.
* GLOBAL SCALE: Architected and launched a global REST API (Typescript/AWS) from scratch handling 1,000+ TPS across multiple regions for 100M+ MAUs with 100% availability since launch.
* AI INNOVATION: Won company hackathon for an AI-powered codebase assistant (Vector search/RAG) now used by 50+ engineers across 4 orgs to accelerate onboarding for large codebases.
* PRODUCT GROWTH: Founding engineer for the Automotive platform; scaled from 200K to 10M+ MAU and led the backend technical expansion from 1 to 3 engineering teams (20+ devs).
* INFRASTRUCTURE MODERNIZATION: Re-architected a legacy monolith into 4 isolated CDK applications, slashing deployment cycles from weekly to under 1 hour and reducing QA overhead by 60%.
* STRATEGIC INFLUENCE: Authored a thorough technical analysis that secured Director-level alignment for cross-org latency fixes, delivering 300ms+ performance gains for core API experiences.
San Francisco, California, United States
2017 — 2020
San Francisco Bay Area
Designed novel bytecode instrumentation that automatically correlates threads along asynchronous code paths
Ported Network Visibility product from our Java Agent to our .NET Agent and redesigned parts of it to support highly asynchronous software.
Built deployment for Pivotal Cloud Foundry by working with Pivotal engineers, convincing them to re-prioritize their feature development, and becoming the first APM company to use extension buildpacks on windows.
Took charge of automatic Java code translation and implemented my ideas to enhance the process, greatly reducing our team’s biggest pain point.
Won 2017 company Hackathon with a facial emotion detection project
San Francisco Bay Area
Designed software to identify high-potential, expansion-stage startup companies.
Built and trained an ensemble of machine learning models to classify and score companies.
Used social network analysis to study syndicate relationships and score quality of investors.
Partners demonstrated my project to potential LP's as they did fund raising
Investing team uses the software in weekly meetings to discover promising companies
Education
2013 — 2017
Carnegie Mellon University
Bachelor's Degree
2013 — 2017