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.

• 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

• 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