Sravankumar Nandamuri is a distinguished technology leader whose innovations have played a key role in transforming the AI, distributed computing, and financial systems landscapes. Currently a Quantitative Developer at Citadel, he specializes in developing high-performance platforms that power next-generation quantitative research and trading. With a career marked by groundbreaking work at leading technology firms, Sravankumar exemplifies how engineering excellence and strategic vision can drive impact at scale.
Early Life and Academic Foundation
Sravankumar’s path to innovation was grounded in a solid academic foundation. He earned his Bachelor of Engineering in Mathematics and Computing from the Indian Institute of Technology (IIT) Guwahati in 2011, one of India’s top engineering institutions. His education combined rigorous training in both mathematics and computer science, offering him a dual focus that uniquely positioned him for solving complex engineering problems. Graduating with a GPA of 8.0 out of 10, he demonstrated early on a mastery of theoretical principles and practical problem-solving.
At IIT, he developed a strong appreciation for algorithmic thinking and data modeling. This early exposure to the interplay between computation and mathematics laid the groundwork for a career centered around scalable system design, intelligent automation, and data-driven insights. His academic background continues to influence his approach to building systems that are both efficient and robust.
Professional Journey
Sravankumar began his career at Amazon in 2011, where he made immediate contributions to large-scale infrastructure. He was a founding engineer of AWS IoT Things Graph, later branded AWS IoT TwinMaker. He led the architecture of a powerful workflow execution engine that enabled developers to connect IoT devices with ease. His role extended beyond implementation to defining product scope, conducting research, and leading a delivery team.
He also worked on AWS DynamoDB Accelerator (DAX), optimizing the system to achieve over 1 million reads per second. His improvements to its fault tolerance and performance helped establish it as one of the most efficient caching layers in cloud computing. His work combined deep systems knowledge with a sharp focus on end-user experience and operational reliability.
In 2019, Sravankumar joined Meta (formerly Facebook), where he led the ML Data Platform team. There, he designed scalable pipelines to support large-scale model training, developed feature monitoring systems, and introduced advanced fault-tolerant mechanisms. His contributions boosted training reliability by up to 40 percent for models critical to Ads and Feed ranking, ensuring high-quality AI output.
At Snowflake from 2022 to 2025, he led the Machine Learning Platform team. He spearheaded the strategy and execution of scalable AI training infrastructure, launched the Snowpark ML Modeling API, and introduced the Snowflake Container Runtime for distributed GPU-based training.
Leadership and Innovation
Sravankumar is known for a leadership style rooted in technical depth, collaborative engagement, and strategic foresight. He excels at guiding cross-functional teams through complex design challenges while fostering a culture of innovation. His hands-on approach allows him to translate high-level goals into well-architected, production-ready systems. At every company he’s been a part of, he has demonstrated an exceptional ability to align technical design with business needs.
His role often bridges the gap between engineering, research, and product development, allowing teams to iterate rapidly while maintaining stability and performance. His leadership has proven vital in enabling organizations to bring state-of-the-art AI capabilities into production environments.
Notable Achievements
Among his many achievements, Sravankumar’s contributions to DAX and AWS IoT TwinMaker stand out as foundational to modern cloud infrastructure. At Meta, his work improved the reliability of mission-critical AI systems. At Snowflake, he played a central role in building one of the most widely adopted AI platforms in cloud analytics.
Academic Contributions
Though primarily an industry practitioner, Sravankumar continues to apply academic rigor to real-world problems. He has contributed to research-oriented efforts, such as verification frameworks for distributed systems and sampling techniques for clustering telecom data. His work exemplifies how theory can directly inform practical innovation.
Future Vision and Impact
At Citadel, Sravankumar is building world-class research platforms that enable fast, reliable backtesting and model deployment. His work at the convergence of scalable systems and financial modeling continues to shape the future of quantitative trading. As industries increasingly integrate AI into their core strategies, his contributions will remain central to advancing performance, reliability, and innovation.
