Adit Madan is a product-focused engineering leader and Co-Founder & CTO with a decade of experience building cloud-native, data and AI infrastructure from research prototypes to commercial platforms. He led product and growth at Alluxio—helping drive 3x ARR growth two years running—and was a top contributor and PMC member on the Alluxio open-source project that powers data orchestration for large-scale ML and analytics. His background blends distributed systems engineering (early Alluxio tech lead, Swift connector refactors) with research experience at Hewlett-Packard Labs and IBM Research, and advanced training in big data systems from Carnegie Mellon and IIT Delhi. Based in San Francisco, he specializes in scalable AI platforms, data lakes, distributed storage and full-cycle AI product engineering, with a track record of translating deep technical work into multi-million dollar enterprise outcomes. A less obvious strength is his hands-on history across the stack—from low-level storage I/O and object-store integrations to cross-functional GTM and product strategy—making him comfortable switching between code, architecture and business.
9 years of coding experience
14 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)
Master's degree Computational Data Science - Big Data Systems, Master's degree Computational Data Science - Big Data Systems at Carnegie Mellon University
Alluxio, data orchestration for analytics and machine learning in the cloud
Role in this project:
Back-end Developer
Contributions:80 reviews, 1052 commits, 389 PRs in 5 years 3 months
Contributions summary:Adit primarily contributed to refactoring and improving the stability of the Alluxio Swift under file system connector. Their work involved refactoring code to utilize common utility functions, renaming methods, and improving efficiency in operations such as file listing, deletion, and rename. They demonstrated expertise in handling Swift object storage interactions, making improvements to the handling of paths, file metadata and the underlying I/O operations for improved reliability.
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