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The role involves developing Go services and managing high-concurrency routing for AI workloads, integrating with various APIs and systems, and ensuring compliance under real load conditions.

The role involves building and maintaining a distributed AI scheduling layer using Ray and Kubernetes. Responsibilities include creating Ray-based task graphs, optimizing workload drivers, and ensuring efficient scheduling and resource utilization for AI tasks.

The role involves developing Kong or OpenResty plugins in Lua, managing API gateway functionalities, ensuring low-latency interactions, and maintaining high performance and observability in production environments.

The role involves building a Go-based control plane for managing Kubernetes clusters, ensuring control-plane reliability, and integrating with OS and workload layers.

The role involves building CI/CD pipelines for Linux OS images, configuring PXE boot infrastructure, and managing container image workflows.

The role requires building gRPC and REST APIs for Kubernetes provisioning, managing namespaces, and running integration tests, among other responsibilities.