Led team of 5 engineers to build Rules Engine that executes 20+ daily rules, generating 1,096 tickets for hardware recovery resulting in an estimated $40M+ savings

Achieved $15M+ annual cost savings by designing and developing a data streaming service which analyzes 50000+ AWS accounts every day

Partnered with two Principal Engineers to design and develop a system reducing MTTR by posting deployments, experiments, and config changes with service metrics to tickets within 60 seconds reducing high severity incident resolution time by 60%

Designed and implemented an annotation system to visualize change events on metric timelines, achieving 100% retention across 130+ onboarded services; the tool served the entire Amazon Ads org and automated service topology generation.

Designed and Developed an integration between internal incident management system and customer facing console reducing communication time from 3 days to 10 minutes.

Led the migration of incident management portal from a monolithic front end architecture to a micro frontend framework reducing the deployment time of independent apps from multiple days to minutes

Created a forecast management tool which allowed teams to plan hardware requirements up to 24 months into the future and reduced the effort per planning cycle from 7 weeks to 2 days

Designed the overall service architecture and pipeline for Amazon’s Employee Self Service Portal using API Gateway, AWS AppSync and other AWS serverless services, expected to serve around 1 million customers

Designed and developed a direct S3 integration from Salesforce, saving storage costs on Salesforce, around 10000 files are uploaded each day on this S3 bucket

Architected the distributed deployment of Splunk instances for monitoring and alerting purposes using ALBs and EC2 instances. This deployment logs 600 GB a day into our Splunk instances

Improved the stability of the existing Android automation framework, which resulted in lower number of test cases in manual testing queue

Developed a stress testing framework to help test up-to 1000 simultaneous connections with total calls exceeding 1 million using AWS Lambda and custom code written in Python

Increased build verification test coverage for Android, iOS, Mac, Windows and Web Frameworks to 90%

Consistently worked on 5 different frameworks each written in a different language for e.g. Android was written in Kotlin, iOS was written in SWIFT, Windows and Mac were written in Python and Web Framework was written in Java

Parallelized the automation framework to reduce the running time from 6 hours to 40 minutes

Increased the flexibility of the Framework by using Force.com Partner API and SOQL to feed data to the framework, this helped the framework

Developed Python scripts to automate various tasks, which allowed Manual testers to concentrate on Sprint Testing

Automated 70% of the regression scenarios in a month, while reducing brittleness of the framework

Implementation of the framework reduced the time required to perform regression testing by 50%, saving 96 person hours for each sprint

Developed Visualforce pages and Apex controllers for a document generation module on SFDC for a client

Deployed Apex classes, Visualforce pages, Standard and Custom objects and Workflows to a test environment using the Force.com IDE

Implemented Schedulable Batch Apex classes and Triggers to perform

Designed a Genetic Algorithm which formulated approximate multi-bit adders which lowered the power consumption (C++)

Verified the functionality (Functional Coverage) of a three port router with a test bench created using UVM techniques (Specman ‘e’)