- Define and execute the roadmap for managed Kubernetes, managed Slurm services, SUNK, and Run:ai integration
- Own the end-to-end cluster lifecycle, including provisioning, configuration, upgrades, scaling, high availability, and decommissioning
- Establish scheduling and resource management capabilities for GPU workloads, including quotas, fair-share policies, multi-tenant isolation, and priority handling
- Drive integration between orchestration services and core infrastructure components, including networking, storage, identity, observability, and billing systems
- Define service-level objectives for control plane reliability, job scheduling latency, cluster availability, and upgrade stability
- Design APIs, CLI tooling, and UI workflows that enable self-service cluster management and workload operations
- Partner with customer-facing teams to understand training, inference, and HPC use cases, translating real workload requirements into product capabilities
- Monitor industry trends in container orchestration, HPC scheduling, distributed systems, and AI infrastructure to inform product direction
KubernetesProduct ManagementDistributed Systems