Monetization

• Led development of Amazon’s internal project management platform—built a full-stack, centralized system for project lifecycle management with features like resource uploads, commenting, permissions, notifications, and approvals. Used S3, DynamoDB, Lambda, and EventBridge to improve team collaboration and visibility.

• Lead developer for Amazon’s internal data hub—delivered a centralized data visualization platform with permission management, multi-source integration, and a data marketplace. Leveraged Redshift, Firehose, SQS/SNS, Glue, StepFunction, Athena, EventBridge, and QuickSight to empower business groups with critical insights.

• Built high-scale real-time and batch metrics infrastructure using CloudWatch, Lambda, Kinesis, Timestream, and S3. Enabled customers like Slack and Chime to monitor media quality, improve product design, and maintain high service SLAs.

• Designed and led development of video ad revenue consolidation pipeline—automated revenue attribution for 1.5K+ ad spaces/min, enabling dynamic ad buying and generating $500M+ in annual revenue.

• Designed and lead development of distributed Container Agent Service that runs on 100k+ nodes to provision docker containers that empowers 1.5M+ (and counting) business critical services from Bing, Office 365, Xbox etc. The service helped achieve 10X+ scalability and 3X+ increase in resource utilization.

• Architected and lead development of the Availability Management Service (AMS) that monitors, diagnose and reports node health status of 2M+ azure nodes that powers the whole Microsoft ecosystem. The service improved node availability by 4 standard deviations (97% to four 9s) and reduced engineering hours spent on livesite investigations by 90%.

• Architected and developed software algorithm and efficient data structures for the RC extraction software which guarantees fast analysis time and accurate RC model for designs.

• mplemented algorithmic optimization to reduce the memory usage by 90% without runtime/accuracy loss.

• Lead developer for the in-house transistor-level power analysis software. The software guarantees fast analysis time and generates accurate power model for custom designs.

• Developed save/restore mechanism for the power analysis software which improves the runtime by over 70%.

• Cooperated with other companies on the integration of the software and the APIs to allow users to have multiple options for power characterization engines. This implementation also helps with debug and verifications.