Rajarshi Tarafdar

Senior Software Engineer-GenAI
JP Morgan Chase

Rajarshi Tarafdar is an accomplished AI Infrastructure Engineer specializing in Generative AI, Cloud Computing, and Enterprise Model Integration. With over nine years of experience, he has contributed to AI-driven development, cloud infrastructure, and large-scale enterprise system optimization. He currently serves as an Associate Software Engineer III – Generative AI at JPMorgan Chase, where he plays a pivotal role in developing AI-powered developer tools and driving enterprise cloud transformations. Throughout his career, he has worked with some of the world’s most innovative organizations, including JPMorgan Chase, BlueCross Blue Shield (Cognizant), Genentech, Symantec, University of Missouri, Kansas City and Capgemini Rajarshi holds a Master of Science in Computer Science from the University of Missouri – Kansas City, where he focused on AI-driven automation and cloud-based computing solutions. He also earned PGDM in Data Science from IIIT Bangalore and B.Tech in Computer Science and Engineering from the West Bengal University of Technology – Kolkata, which laid the foundation for his expertise in software engineering, data processing, and distributed systems.

His extensive academic background, combined with his industry experience, enables him to critically evaluate research contributions in AI, cloud computing, and enterprise systems.

Rajarshi Tarafdar’s Session

1:00 p.m.–1:45 p.m. PT — Thursday, September 18, 2025

Best Practices for Enterprise Integration of AI Agents

As AI agents move from concept to enterprise reality, the challenge shifts from “should we adopt them?” to “how do we integrate them effectively?” This panel dives into the tactical and technical best practices for embedding AI agents into existing systems, workflows, and teams. Panelists will explore how to navigate cross-functional collaboration between product, engineering, and data teams; design AI agent architectures that balance autonomy with oversight; and address emerging concerns around traceability, security, and ethical behavior. With examples spanning data management, healthcare, and more, this session focuses on how to move from experimentation to execution—ensuring your AI agents are not only deployed, but delivering measurable value at scale.

Check out our early bird ticket prices!