Senior AI Infrastructure Engineer, Cloud Partnerships - DGX Cloud at NVIDIA

Santa Clara, California, United States

NVIDIA Logo
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Technology, AI, Cloud ComputingIndustries

Requirements

  • 8+ years of experience in infrastructure architecture, cloud native, or large-scale platform/reliability roles
  • Bachelor's degree or equivalent experience
  • Experience designing scalable, maintainable backend systems and writing clear design documentation
  • Strong understanding of multiple cloud infrastructure provider resource offerings
  • Demonstrated experience in normalizing and unifying diverse data sources from a variety of systems into broadly applicable schemas, enabling efficient querying and analysis
  • Proven ability to lead and influence cross-functional technical initiatives at scale across vendors and external partners, especially in reliability or platform domains
  • Demonstrated ability to design and implement maintainable APIs for internal and external customers
  • Proficiency in Kubernetes administration, modern CI/CD techniques and Infrastructure as Code (IaC)
  • Experience building resilient production systems using Golang, Python or Ruby
  • Experience in delivering production infrastructure across various cloud providers, including hands-on experience in building and managing this infrastructure, as well as managing vendor relationships

Responsibilities

  • Architect unified systems for integrating infrastructure provider maintenance events into NVIDIA engineering systems
  • Drive the adoption of operational excellence best practices across all infrastructure providers, partnering with SRE, infra, product, and security teams
  • Define and operationalize governance models for engineering support engagements, infrastructure maintenance lifecycles, and incident escalation paths
  • Measure provider availability against projected maintenance schedules using Service Level Objectives (SLOs)
  • Collaborate with AI/ML teams to integrate intelligent automation into maintenance workflows, such as projecting job capacity impact based on scheduled resource availability and suggesting infrastructure reallocations for high-profile initiatives
  • Develop a long-term roadmap to guide infrastructure providers in progressively adopting best practices for reliability and production hygiene across existing and new product introductions

Skills

AI Infrastructure
Cloud Native
API Integrations
SRE
SLOs
Backend Systems
Infrastructure Architecture
Vendor Management
Automation
ML Workflows

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters
1993Year Founded
$19.5MTotal Funding
IPOCompany Stage
Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries
10,001+Employees

Benefits

Company Equity
401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.
Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.
Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.
NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.
Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.
Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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