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

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AIIndustries

Requirements

8+ years of software engineering experience, with deep expertise in backend systems and infrastructure
Bachelor's degree or equivalent experience
Strong proficiency in Python and Go, with a track record of delivering reliable, scalable software solutions
Experience designing scalable, maintainable backend systems and writing clear design documentation
Deep experience with Kubernetes and cloud-native infrastructure
Experience working with building, deploying, and maintaining ML models in production systems
Familiarity with AI agent frameworks or orchestration tools
Solid understanding of system observability, monitoring, and performance optimization
Strong collaboration and communication skills to work across remote teams

Responsibilities

Build AI-powered tools that enhance operational excellence by leveraging diverse operational data, supporting incident, change, and problem management workflows
Collaborate closely with Incident Commanders, incident response, and SRE teams to integrate AI-driven automation and analytics into operational workflows
Design, develop, and maintain backend systems and infrastructure using Go and Python to support internal AI tools and intelligent agents
Build and maintain data pipelines using PySpark and related tools to support AI and analytics workflows
Operate and scale infrastructure using Kubernetes, managing containerized AI services and automating pipeline deployments
Work with vector databases to enable semantic search and retrieval-augmented generation use cases
Integrate large language models, agent systems, and classical ML models into internal services and automation workflows
Improve observability, deployment automation, and system reliability for AI-driven services

Skills

Key technologies and capabilities for this role

GoPythonPySparkKubernetesVector DatabasesLLMsAI Agent FrameworksData PipelinesObservability

Questions & Answers

Common questions about this position

What experience level is required for this Senior AI Infrastructure Engineer role?

The role requires 8+ years of software engineering experience with deep expertise in backend systems and infrastructure.

What programming languages and tools are essential for this position?

Strong proficiency in Python and Go is required, along with experience in PySpark for data pipelines, Kubernetes for infrastructure, and vector databases.

Is this a remote position, and what is the work arrangement?

The job involves working across remote teams, indicating a remote-friendly arrangement with collaboration required.

What salary or compensation is offered for this role?

This information is not specified in the job description.

What experience will make my application stand out for this role?

Proven experience delivering AI-driven features end-to-end from infrastructure design to production deployment, and familiarity with Temporal, Argo, or other workflow engines and vector databases.

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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