Design and develop software features for system resiliency, high availability, and fault-tolerant architecture in distributed environments. Build and maintain cloud-based deployment workflows and APIs for real-time AI inference using AWS and container orchestration.
Implement and optimize high-performance, low-latency inference infrastructure using Kubernetes and Docker. Develop Python-based scripts and APIs to streamline data preprocessing and ensure system reliability through automated monitoring and debugging.
Perform post-silicon validation, testing, and debugging of Wafer Scale Engines to ensure compliance with hardware specifications. Develop automated regression test scripts and debug tools using Python and shell scripts to optimize wafer bring-up flows.
The role serves as the single-threaded owner for delivering end-to-end data center capacity from forecast and design through construction and go-live. It involves orchestrating cross-functional execution across real estate, power, and infrastructure teams to meet aggressive AI system deployment targets.
