• Developed exercise recording feature for computer vision exercises, enabling CV model

development teams to collect significantly more data from real world use cases, allowing for

faster iteration and fine tuning of ML models.

• Deployed necessary AWS infrastructure via Terraform, implemented CI/CD pipelines, and

lead development of APIs for serverless microservice designed to allow the mobile

application to implement dynamic device capability detection, resulting in seamless

onboarding of new devices to the Computer Vision in-app experience and reducing

developer hours required to maintain previous device capability detection code

• Implemented Datadog monitoring and alerting for team-owned services, defining thresholds

for availability, latency, and error rates allowing for early detection of production issues and

integrated alerts with PagerDuty to alert the correct on-call teams when necessary

• Architected backend API solution, led development across multiple microservices, and

coordinated with stakeholders to deliver Computer Vision Movement Analysis feature,

allowing members and care teams to analyze and track member progress with exercises

over time

• Planned development of new product feature set resulting in a 1% increase in exercise

therapy completion rates and enabling an increased level of user-driven personalization in

their exercise therapy

• Created and executed development plan for migration of several features to new event-

driven progress tracking paradigm, maintaining feature parity and enabling faster iteration

on features that deliver a more personalized user experience

• Investigated and implemented performance optimizations for critical API endpoints resulting

in 50% to 90% reduction in latency.

• Developed features and kicked off efforts involving migration of all user data to add more

levels to the app, resulting in 4.5% and 4.7% increase in user retention and engagement

respectively

• Designed and developed new data models and features in our orchestration layer resulting

in launch of new participant programs and enabling internal stakeholders to have an

increased level of customizability of participants' exercise therapy

• Led numerous app releases by cutting and patching release candidates, coordinating with

stakeholders, and ensuring timely delivery of app to iOS and Android app stores

• Developed API frontend in React for internal data movement platform allowing users to

register and manage data sources/sinks resulting in 1M+ messages sent using the

platform and increased data movement and observability across Nike

• Developed full stack web application in React and Flask delivering a premium experience

to interview candidates and allowing them manage itinerary, travel, and navigation around

Nike campus

• Developed features and addressed defects pertaining to the shop and buy experiences in backend services for Nike’s wholesale e-commerce website, nike.net

• Automated processes for deploying and maintaining AWS namespaces for 100+ development teams across Nike

• Created policies to enforce cloud compliance/tagging standards for AWS resources

• Managed deployment and maintenance of cloud compliance software

• Provided AWS and CI/CD pipeline support for various teams across Nike

• Provide technology support for users working in the College of Education building and

taking online classes

• Resolve technology related issues for users in the college

• Teach users how to setup and use classroom technology for presentations, conference

calls, etc.

• Performed analysis and integration of Nike’s vulnerability data collected by Attack

Surface Management team

• Conducted a penetration test and created report of findings for internal website containing

news updates about the company.

• Developed front end of code submission/grading web application used to train developers

on best security practices