• Built RAG pipeline using Elasticsearch search for automated candidate sourcing, boosting approval rates by 54%

• Implemented RBAC authorization enabling enterprise acquisition and $24K+ ARR growth

• Developed LLM-powered real-time candidate qualification summaries aligned to recruiter criteria

• Created recommendation system using logistic regression to optimize AI sourcing agents

• Led development on Expert Eyes released on the Vision Pro

• Developed the AR pinning and recall system

• Implemented AR procedure generation using Deepgram and GPT-4

• Optimized load up times sitewide by 540% while decreasing costs for RDS clusters by 30% through query optimizations, caching, and materialized views in order to unblock multiple enterprise customers

• Improved file ingestion by implementing async processing through S3 uploads with lambda triggers in order to extend accepted file sizes by over 1200%

• Worked end-to-end on a feature to split and parse resume book files to create new candidates and enrich existing candidate profiles using Flask, PyMuPDF, and TextKernel and rolled out the feature internally

• Hosted the entire component library using AWS S3 and CloudFront and handled authentication with Lambda and Cognito in an application which now serves over 3000 requests per month

• Created hoverable candidate profile cards for users to surface important information using React, GraphQL and Flask and rolled out to the 1000+ customer base receiving positive feedback from enterprise customers such as Wayfair and Lyft