HIPAA Compliance - Researched and implemented overarching, cross-team changes to the core product systems in order to provide compliance and acquire new clients, collaborating with a team of 5+ engineers, Legal, and clients directly - Led the production readiness of the design, ensuring an incident-free Beta release and signing off on final alerting, monitoring, smoke testing, and infrastructure preparednessQuality and Release Velocity- Reduced automated test flakiness (false failures) to 0.6% on a monthly basis

Api-Gateway Redesign- Continued rearchitecting and redesigning existing critical edge services from Nginx/Lua into a Golang microservice for increased robustness, reliability, and performance. Scaling to serve 3x the request volume and multiple API endpoints.- Continued to develop requirements using a data-driven approach in order to prevent and recover from incidents faster.Kubernetes Cluster Upgrade- Supported the migration of kubernetes microservices serving billions of requests per day to an AWS EKS Kubernetes cluster, while maintaining latency and uptime SLAsA/B Testing- Introduced and implemented a Proof of Concept for Randomized Controlled Experiments to drive improvements to product KPIs and inform roadmap decisions with statistically significant findings - Initial PoC built in house, then researched various third party tools, selected and implemented one of them and proposed wider adoptionQuality and Release Velocity- Significantly reduced production bugs and incidents with an automated regression testing system integrated with Slack, improving developer ownership of test failures and product quality- Increased release frequency from once per week to multiple times per day, with no decrease in product uptime and reliability

Api-Gateway Redesign- Achieved 4x performance of a critical edge service ingesting billions of event per day by rearchitecting and rewriting it from Nginx/Lua to Golang. Deployed as a microservice to Kubernetes on AWS EC2.- Drove release velocity and confidence by implementing a novel data verification system to safely test the new component against real-time production data in an isolated manner.- Enabled data-driven design of the new system by first analyzing 16 months of past incidents to identify and communicate major bottlenecks and risks.Abuse and Fraud Protection- Saved millions of dollars per year in infrastructure costs by building and maintaining systems and tooling to counteract abusive and fraudulent product usage.- Implemented an instantaneous, multi-dimensional event counting and blocking mechanism using Redis (AWS Elasticache) and Nginx/Lua.

Increased Cost Efficiency and Stability of Production Systems- Integrated tools such as horizontal+vertical autoscaling and spot instances into applications running on Kubernetes on AWS EC2 to improve cost efficiency, maintainability, and stability.- Led a month long, cross-team initiative to clean up references to old infrastructure and tooling to enable the safe decommissioning of these tools to regain millions of dollars per year.Developed new features for Java, NodeJS, Lua/Nginx microservices deployed to Kubernetes on AWS EC2Performed oncall and site-reliability duties as needed in a distributed, microservice environment

Kubernetes, Docker, FluentBit, Java, NodeJS, Kafka

Go, Kafka, AWS, PostgreSQL

Python, statistical analysis, imaging algorithms

R, C#, statistical analysis, imaging algorithms