• Engineered an LLM-powered medical document interpreter leveraging various prompt engineering techniques and GCP VertexAI and RAG engine, while increasing accuracy through integration of proprietary knowledge

• Designed and implemented a HIPAA-compliant AI interpretation publishing system using React, TypeScript, and Figma, reducing staff workload by 47% (21 minutes to 10 minutes per interpretation) and streamlining staff UX and onboarding experience to a few clicks of a button

• Accelerated the release cycle by 40% by architecting a hybrid QA framework using Playwright, automating repetitive E2E paths while maintaining manual testing for ever-changing, complex clinical workflows

• Integrated various 3rd party platforms into tech stack and between each other to efficiently streamline medical staff workflows

• Owned product end-to-end for an AI press-monitoring and digest product (industry/financial analysts): set vision and positioning, ran customer discovery and interviews, and prioritized what to ship first—monitoring, summarization, and email digests.

• Architected the backend and delivery pipeline in Java on AWS (RDS PostgreSQL, Lambda, API Gateway): change detection on monitored press-release sources, LLM-generated summaries, relational storage, and scheduled runs plus personalized digest and newsletter flows.

• Designed and shipped the customer experience in Next.js/React and TypeScript: marketing site, auth, and user/admin dashboards from Figma, integrated with the REST API and deployed on Amplify alongside the serverless stack.

• Implemented testing suite for web app used by Fortune 500 Companies using Python and Robot Framework, allowing for QA testers to create E2E tests from a CSV file

• Collaborated with 5 other interns to research and propose 2 unique product concepts to Zebra stakeholders

• Strengthened and added user experience features on an admin panel for mobile app using Firebase, Figma, and low-code platform