sumtatt

At Snowflake, my recent engagement involves building internal efficiency tools for the CXE team, enhancing developer productivity, and streamlining workflows for our Cortex search APIs. A key focus has been having improved quality of product along with optimizing our CI/CD pipeline, ensuring faster feedback loops and reducing bottlenecks in deployment cycles. This initiative has significantly improved our support engineering processes, enabling engineers to diagnose and resolve customer issues with greater speed and accuracy. 

Previously, at Fiddler AI, I led efforts to develop internal tooling that accelerated product releases and quality assurance. I designed and implemented scalability and upgrade testing frameworks, not just for validation but to automate and simplify performance monitoring and release workflows. These tools played a crucial role in ensuring seamless ML model deployments, reinforcing key principles like observability, explainability, and compliance. 

By integrating Python, Golang, Kubernetes, and cloud technologies, I have consistently delivered automation-first solutions that enhance engineering efficiency, minimize manual effort, and drive operational excellence.