NVIDIA
Enterprise AI
SeniorTechnicalProductManager–DGXEnterpriseInfrastructureandCloudNativeOperations
“Senior Technical Product Manager – DGX Enterprise Infrastructure and Cloud-Native Operations at NVIDIA. Skills: Product Management, Enterprise AI, DGX Enterprise Infrastructure, Cloud-Native Operations, Kubernetes, On-Premise Infrastructure Management. set the vision for the Enterprise Operational Gold Standard. define how the world’s most sophisticated companies deploy, manage, and scale their Enterprise AI Factories”
What You'll Achieve.
deliver the "NVIDIA Experience" within the customer’s data center; ensure that every enterprise DGX deployment is standardized, repeatable, and resilient; keep the fleet at peak performance without manual intervention
Industry & Context.
How do you make a 1, 000-node private cluster feel as fluid, scalable, and invisible as the public cloud?; When a job slows down in a private data center, your framework should provide the "one-click" answer—isolating a thermal throttle, a degraded InfiniBand rail, or a cabling fault instantly; eliminate "management snowflakes"
What They're Looking For.
Must Have
12+ years demonstrated ability in Product Management, specific around on-premise infrastructure, private cloud, or large-scale systems management, Bachelors Degree in Computer Science or related field or equivalent experience, The "Platform-First" Approach: A track record of turning complex hardware operations into software-defined workflows, Cloud-Native Expertise: Expert-level understanding of Kubernetes operators, container orchestration, and how to translate physical hardware constraints into declarative code, Operational Scars: You’ve lived through the challenges of managing large-scale Linux fleets in air-gapped or restricted enterprise environments, Technical Breadth: Deep familiarity with data center networking (InfiniBand/Ethernet), storage architectures, and the firmware-to-OS handshake, Leadership & Evolution: This is a high-visibility role at the intersection of multiple engineering fields, explicit expectation to transition into formal people management as the team expands
Nice to Have
Automation Evangelist: You have experience with infrastructure-as-code (Ansible, Terraform, Pulumi) in a bare-metal context, AIOps Pioneer: You have a vision for using AI to manage AI—applying telemetry and machine learning to predict and prevent infrastructure failures
What You'll Do.
set the vision for the Enterprise Operational Gold Standard
define how the world’s most sophisticated companies deploy
and scale their Enterprise AI Factories
Productize the On-Prem Lifecycle
Build the "Pit Crew" (Observability)
Bridge Hardware to Kubernetes
Drive Predictive Operations
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