Atul Triplicane

About Atul Triplicane

I have a strong interest in building intelligent, data-driven systems, intersecting Software Engineering and AI. This past summer, I worked as a Machine Learning Engineer Intern at Cisco Webex, where I helped develop AI agents and Model Context Protocol (MCP) servers enabling natural language to SQL query generation, dynamic visualizations, and real-time insights across large datasets. I also co-led the development of Collaboration Canvas, an internal productivity tool integrating Webex and Outlook data to summarize unread messages, meetings, and action items, working closely with product managers and design teams to refine the user experience. I’ve also served as a Teaching Assistant for CSC 210 (Software Development in Java), where I supported students with debugging, object-oriented design, and algorithmic problem solving, strengthening both my technical depth and my ability to communicate complex ideas clearly. I’m particularly drawn to roles that combine software engineering with applied AI and data driven decision making, and I’m motivated by building scalable, human centered systems that turn complex data into meaningful, usable solutions.

Experience

1. Applied Ai Evaluator

   Alignerr

   Feb 2026 — Present

Education

• University of Arizona

  Bachelor of Science - BS, Computer Science

• Candor International School

  IB Diploma & Cambridge IGCSE, High School