Building classifiers for Youth ML

Previously, worked on AI infrastructure for recommendation systems

• Improved observability of customer journeys by implementing a top-level workflow identifier for end-to-end interaction tracking.

• Contributed to re-architecting the checkout service, significantly enhancing scalability, reliability, and maintainability of critical transaction flows.

• Built a graph-based data discovery POC using enterprise ontology and Amazon Neptune, enabling unified querying across disparate datasets via SPARQL

• Drove product direction through stakeholder interviews, defining roadmap for enterprise data discovery platform

• Optimized streaming pipelines by introducing feature extraction in filter expressions, reducing payload size and storage costs

• Migrated APM metrics from Splunk to New Relic, improving monitoring latency and system observability

• Mentored junior engineers through bi-weekly career development sessions

• Led design of a multi-region, active-active serverless config platform (AWS Lambda, SQS, DynamoDB/DAX), enabling zero-downtime updates across microservices

• Built A/B experimentation framework for Eno, accelerating iteration on user experiences across channels

• Evaluated and drove adoption of DynamoDB DAX over Redis, influencing org-wide caching strategy

• Served as CMU campus ambassador, supporting recruiting and university engagement