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$177,250–$235,750.
Based on 240 similar postings.
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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
Senior Technical Product Manager – DGX Enterprise Infrastructure and Cloud-Native Operations joins the team to architect the operational future of Enterprise AI. This role involves defining the software-defined blueprint that transforms raw DGX hardware into high-availability, self-healing AI Factories. You will productize the on-premise lifecycle for DGX SuperPODs, managing bare-metal provisioning, network fabric configuration, and automated firmware rollouts. Key responsibilities include building telemetry and diagnostic suites for observability, integrating DGX systems into cloud-native ecosystems, and developing APIs and services to standardize large-scale deployments. Required expertise includes Kubernetes operators, container orchestration, data center networking like InfiniBand and Ethernet, and storage architectures. You will solve the challenge of making large-scale private clusters feel as fluid and scalable as public clouds through automated health checks and predictive operations.
What does a Technical Product Manager earn in California?
Median $200000 from 31 postings across 11 companies.
Define the "Day 0 through Day 2" lifecycle for DGX SuperPODs, including bare-metal provisioning and firmware rollouts.
Develop a telemetry and diagnostic suite to provide instant identification of hardware and network faults.
Lead the integration of DGX systems into cloud-native ecosystems like Kubernetes for seamless multi-node scaling.
Build APIs and services to standardize and repeat enterprise DGX deployments while eliminating manual configurations.
Define features for automated health checks to transition infrastructure from reactive maintenance to self-healing operations.
Translate physical hardware constraints into declarative code for large-scale private data center environments.
What we're looking for
12+ years of demonstrated ability in Product Management with experience in on-premise infrastructure, private cloud, or large-scale systems management.
Bachelor's Degree in Computer Science or a related field or equivalent experience.
Proven track record of turning complex hardware operations into software-defined workflows.
Expert-level understanding of Kubernetes operators, container orchestration, and translating physical hardware constraints into declarative code.
Experience managing large-scale Linux fleets in air-gapped or restricted enterprise environments.
Deep familiarity with data center networking (InfiniBand/Ethernet), storage architectures, and the firmware-to-OS handshake.
Experience with infrastructure-as-code (Ansible, Terraform, Pulumi) in a bare-metal context (preferred).
Vision for using AI to manage AI by applying telemetry and machine learning to predict and prevent infrastructure failures (preferred).
Generative AI
GPU Architecture
AI Inference
Local AI
Linux
Windows
Model Training
Networking
Storage
Security
Simulation
Platform Integration
Software Requirements
Data Architecture
SQL
Data Governance
Data Contracts
Data Catalog
AI
ML
Cloud Infrastructure
GPU
HPC
Observability
Attribute-Based Access Control
Data Modeling
CMDB
Retrieval
Graph-backed Context
Machine Learning
Deep Learning
Artificial Intelligence
Kubernetes
Linux
Cloud Infrastructure
Distributed Systems
SDN
System Integration
Agile
Software Development Lifecycle
Networking
Bare Metal