Working on our Chat AI team
Decreased chat latency by 25% by identifying LLM inference latency due to bloated responses
Added the ability to have cost attribution for our in house model provider service. This allows us to see spend across our different models, products and vendors and identify cost improvements
Improved our agentic retrieval pipeline by parallelizing the rewriting step. This allows us to better target the source systems and write more optimized queries for each data store.
New York, NY
Rearchitected and scaled our Postgres layer to reduce daily outages due to connection issues. Implemented a highly available pgbouncer setup in Kubernetes with a passive failover to handle regional failures. Has allowed us to greatly scale our read and write volume to our primary instance with no incidents.
Eliminated single points of failures for our Postgres read replicas and migrated us to DNS for our load balancing. This led to 50% faster p95 and reduced costs due to reduced cross region data transfer.
Championed and introduced distributed tracing to our stack, instrumenting all services to give all teams visibility into transactions. Did this by introducing opentelemetry as the standard framework.
Managed datadog spend, implemented multiple cost reduction improvements around custom metrics and APM.
Reduced Snowflake costs by 50% by analyzing query patterns and implementing clustering keys to reduce warehouse usage.
2023 — 2024
Engineering Team Lead of Analytics
* Led the development and launch of a Universal Analytics Events API, capable of ingesting thousands of user events per second. This enhancement significantly improved error reporting and increased developer friendliness. It enabled new teams to launch real-time analytics for their products within days, a substantial improvement from the weeks required with the old system.
* Led the development of SLOs (Service Level Objectives) for our core service, helping to alert teams when customers faced data delays.
* Migrated multiple daily batch jobs to airflow, simplifying the data model and greatly reducing cost on our warehouse spend.
* Facilitated bi-weekly scrum practices with planning, estimation, and retrospectives. Focused on singular sprint goals and driving the team to work on a single project at once, which significantly improved the overall team velocity.
* Implemented new team practices to manage alerting and maintain consistent oversight of our system health. This resulted in a more manageable overall volume of alerts and a significantly better signal-to-noise ratio.
2023 — 2023
2019 — 2023
New York, New York
Prototyped KafkaConnect for the company; Currently being used to stream messages from Amazon SQS to Kafka. Handling over 40 million messages per day.
Owned Intelligent Search Tracker, a large scale data scraping service. Interfaced with third party vendors to handle data integrity issues and increase reliability.
Designed a system to automatically propagate data delays from source data systems and surface that to customers.
Deployed tracing system for our deployment pipeline to help aggregate deployment issues at scale.
Education
2015 — 2019
Carnegie Mellon University
Bachelor of Science (B.S.)
2015 — 2019
2011 — 2015
Methacton High School
2011 — 2015