Teams at NVIDIA

Develop and optimize resilient, large-scale cloud services supporting AI training workloads. Design Kubernetes-orchestrated microservices, APIs, job submission abstractions, lifecycle automation, checkpointing, telemetry, and failure recovery systems. Collaborate on distributed systems spanning cloud and on-premises AI clusters, integrating with NVIDIA resiliency infrastructure and HPC platforms. The role requires backend development experience, cloud and container expertise, and familiarity with AI frameworks, schedulers, GPUs, and high-performance computing.

Leads NVIDIA’s internal S3-compatible distributed object storage platform team, owning roadmap execution, software development, production operations, reliability, scalability, and service delivery at exabyte scale. Responsibilities include managing and developing engineering talent, driving SLOs, capacity planning, incident response, CI/CD, observability, customer collaboration, and AI-assisted development adoption. The role requires deep distributed storage expertise and hands-on experience operating cloud storage services for large-scale AI infrastructure.

Build, validate, deploy, tune, monitor, and retire high-confidence security detections across SIEM, endpoint, cloud, identity, SaaS, developer, and AI environments. Translate incidents, threat intelligence, hunts, and red-team findings into tested detection logic. Improve detection-as-code workflows, telemetry quality, coverage tracking, and alert context while reducing false positives. Partner with responders and security teams, conduct reviews, document operational content, and coach analysts and engineers.