NVIDIA

Senior Director, Enterprise AI Factories Deployment

Santa Clara, California, United States

Not SpecifiedCompensation
Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Biotechnology, Artificial Intelligence, Data CenterIndustries

Requirements

Candidates should possess over 18 years of Systems/Solution Engineering experience with a strong hands-on approach and expertise in data center design and operations. A BS, MS, or Ph.D. in Engineering, Mathematics, Physics, Computer Science, Data Science, or a related field, or equivalent experience, is required. The role demands 8+ years of management experience, deep knowledge of CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers. Familiarity with networking switches (Ethernet/Infiniband), data center infrastructure (power/cooling), and DevOps/MLOps technologies like Docker and Kubernetes is essential. Strong operational understanding of large-scale data center infrastructure, including servers, networking, power, and cooling systems, is necessary. Excellent time management, verbal and written communication skills are also required, along with experience managing multi-functional, multi-regional, and supplier-aligned teams.

Responsibilities

The Senior Director, Enterprise AI Factories Deployment will lead the building, scaling, and deployment of AI factories across key enterprise customers, integrating NVIDIA's AI hardware and software technologies into customer data centers. This role involves guiding customer discussions on network design, compute/storage, and supporting server/network/cluster deployments, requiring on-site customer data center visits during the bring-up phase. The individual will act as a trusted technical advisor, demonstrating subject matter expertise in advanced GPU & network systems, and providing recommendations to product teams for roadmap features based on customer requirements. Responsibilities include identifying new project opportunities for NVIDIA products, collaborating closely with GPU/Network Systems Engineering, Product Management, and Sales teams, and conducting regular technical customer meetings for product roadmaps, issue debugging, and new technology introductions. Additionally, the role involves building custom product demonstrations and Proofs of Concept (POCs), hiring and building an elite team of AI Infrastructure architects, and managing the operational backbone for NVIDIA's AI Factory scaling in enterprise environments.

Skills

AI
GPU
Data Center
Networking
Solution Architecture
System Deployment
Product Roadmap
Enterprise AI

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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