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VP, AWS Agentic AI
I run Agentic AI in AWS. My team has launched numerous agentic capabilities that are reshaping the AI landscape. Amazon Quick, launched in October 2025, is AWS's flagship agentic AI application that helps employees transform how they find insights, conduct deep research, automate tasks, visualize data, and take actions across apps. Kiro, the first AI coding tool built around specification-driven development, has been adopted by over million developers and rapidly growing. The agentic stack also includes Amazon Bedrock AgentCore, a comprehensive suite of capabilities for building production-ready AI agents, which launched with features including AgentCore Runtime, Memory, Identity, Code Interpreter, Browser Tool, Gateway, and Observability. Additionally, his team launched DevOps Agent for automating infrastructure operations and Security Agent for proactive threat detection and response. Amazon Transform, AWS's AI-powered data transformation service also includes Transform Custom, an AI-powered code transformation agent that enables customers to create custom code transformation agents for automating organization-specific code maintenance and evolution tasks at scale. I have been awarded (or filed for) more than 250 patents, authored around 40 referred scientific papers and journals, and participate in several academic circles and conferences. In addition to these, I was part of the team that built several AWS Services like CloudFront, Amazon RDS, Amazon S3, Amazon's Paxos based lock service, original Amazon Dynamo etc. I was also one of the main authors for Amazon Dynamo paper (http://bit.ly/1mDs0Yh) along with Werner Vogels. Amazon Dynamo now is the foundation for many other NoSQL systems like Riak, Cassandra and Voldemort.
Vrije Universiteit Amsterdam (VU Amsterdam)
Ph.D., Computer Science
January 1, 2002 – January 1, 2006
Iowa State University
M.S, Computer Engineering
January 1, 2000 – January 1, 2002
College of Engineering Guindy, Chennai
B.E., Computer Science & Engineering
January 1, 1996 – January 1, 2000
UC Berkeley Electrical Engineering & Computer Sciences (EECS)
Board Member, EECS External Advisory Board
March 1, 2026 – Present
Amazon Web Services (AWS)
VP, AWS Agentic AI
March 1, 2025 – Present
Seattle, Washington, United States
National Artificial Intelligence Advisory Committee
Committee Member
May 1, 2022 – May 1, 2025
Amazon Web Services (AWS)
VP, AI and Data
January 1, 2022 – March 1, 2025
Seattle, Washington, United States
Amazon Web Services
VP, Amazon AI
January 1, 2017 – January 1, 2022
Seattle
Amazon Web Services
General Manager, NoSQL and Analytics
April 1, 2012 – December 1, 2015
Amazon Web Services
Sr. Manager, NoSQL
May 1, 2010 – March 1, 2012
Amazon.com
Principal Engineer in Cloud Computing Services
April 1, 2008 – May 1, 2010
Amazon.com
Senior Research Engineer
November 1, 2006 – April 1, 2008
Amazon.com, Distributed Systems Group
Research Engineer Intern
June 1, 2005 – September 1, 2005
IBM T J Watson Research Lab
Software Research Co-op
May 1, 2003 – August 1, 2003
IBM T J Watson Research Lab
Software Research Co-op
May 1, 2002 – August 1, 2002
IBM Linux Kernel Development Labs
Software Intern
May 1, 2001 – August 1, 2001
Cultural Fit Analysis
The candidate's career path at Amazon Web Services, a highly innovative and customer-focused organization, suggests a strong cultural fit for fast-paced, results-driven environments. Their involvement in national and academic advisory roles demonstrates a commitment to advancing technology and contributing to the broader community. The breadth of experience across databases, analytics, machine learning, and distributed systems indicates adaptability and a continuous learning mindset. The leadership roles in building foundational AWS services from the ground up align with a culture that values ownership and pioneering spirit. The target role of Big Data Engineer aligns well with their deep expertise in large-scale data systems and analytics.
Soft Skills & Operational Fit
The candidate's extensive leadership roles at AWS, including VP positions, suggest strong communication, strategic thinking, and operational management skills. Their involvement in advisory committees (NAIAC, UC Berkeley EECS) indicates a collaborative and influential presence in the tech community. The descriptions highlight an ability to build and scale teams and services from scratch, demonstrating initiative and problem-solving capabilities. While direct psychometric test results are unavailable, the career trajectory strongly implies high work attitude, stress handling, and team collaboration in high-stakes environments.