1

Ai Infrastructure Jobs in Raleigh, NC (NOW HIRING)

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams. * Operationalize machine learning workflows and support AI-enabled applications ...

Technical Sales Lead

Morrisville, NC · On-site

$120 - $160/hr

Coordinate technical readiness programs covering GPU compute infrastructure, networking, AI infrastructure validation, performance optimization, cluster deployment, and production readiness.

Senior AI Systems Engineer

Raleigh, NC · On-site

$92K - $126K/yr

Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams. * Operationalize machine learning workflows and support AI-enabled applications ...

next page

Showing results 1-20

Ai Infrastructure information

See Raleigh, NC salary details

$27

$57

$84

How much do ai infrastructure jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for ai infrastructure in Raleigh, NC is $57.53, according to ZipRecruiter salary data. Most workers in this role earn between $46.73 and $67.07 per hour, depending on experience, location, and employer.

What is AI infrastructure?

AI infrastructure refers to the combination of hardware, software, and cloud-based solutions that support the development, deployment, and scaling of artificial intelligence applications. It includes components such as GPUs, CPUs, storage systems, networking, data management tools, and machine learning frameworks. The goal of AI infrastructure is to provide the computational power and resources needed to train, test, and run AI models efficiently, whether on-premises or in the cloud. Organizations invest in robust AI infrastructure to accelerate innovation, manage large datasets, and ensure the reliability of their AI systems.

What are the key skills and qualifications needed to thrive in AI infrastructure?

To thrive in AI Infrastructure, you need expertise in software engineering, distributed systems, cloud platforms, and a solid understanding of machine learning workflows, often supported by degrees in computer science or related fields. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud services (AWS, GCP, Azure), as well as experience with CI/CD pipelines and monitoring systems, is essential. Strong problem-solving abilities, effective communication, and adaptability help professionals excel in cross-functional teams and rapidly evolving environments. These skills and qualities are crucial for building scalable, reliable systems that power AI applications and support organizational innovation.

What are common challenges faced by professionals working in AI infrastructure roles, and how can they be addressed?

Professionals in AI Infrastructure roles often encounter challenges related to scalability, system reliability, and integration with existing IT environments. Managing rapidly growing datasets and ensuring seamless deployment of machine learning models can be complex, requiring robust automation and monitoring tools. Collaboration with data scientists, software engineers, and DevOps teams is critical to ensure infrastructure meets the evolving needs of AI projects. Staying updated with the latest cloud technologies and best practices can help address these challenges and drive successful AI implementations.

What is the difference between Ai Infrastructure vs Data Engineer?

AspectAi InfrastructureData Engineer
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of cloud platforms and AI toolsBachelor's in CS, Data Science, or related; programming and database skills
Work EnvironmentCloud environments, AI model deployment, infrastructure setupData pipelines, database management, data processing
Employer & Industry UsageTech companies, AI startups, cloud providersTech firms, finance, healthcare, e-commerce

Ai Infrastructure professionals focus on building and maintaining the hardware and software systems that support AI models, while Data Engineers develop and manage data pipelines and databases. Both roles require technical skills and often collaborate but serve different core functions within AI and data ecosystems.

What are AI infrastructure jobs?

AI infrastructure jobs involve designing, building, and maintaining the hardware, software, and network systems necessary to support artificial intelligence applications. These roles often require knowledge of cloud computing, data centers, machine learning frameworks, and system optimization to ensure reliable and efficient AI model deployment and operation.

What are popular job titles related to Ai Infrastructure jobs in Raleigh, NC?

For Ai Infrastructure jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Ai Infrastructure jobs in Raleigh, NC look for?

The top searched job categories for Ai Infrastructure jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Ai Infrastructure jobs?

Cities near Raleigh, NC with the most Ai Infrastructure job openings:

Infographic showing various Ai Infrastructure job openings in Raleigh, NC as of August 2026, with employment types broken down into 77% Full Time, 20% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $105,721 per year, or $50.8 per hour.

Senior AI infrastructure engineer - EDA Infrastructure

Nvidia

Durham, NC • On-site

$104K - $142K/yr

Full-time

Posted 2 days ago

New


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

AI Infrastructure Engineers at NVIDIA build the systems, tooling, and data infrastructure that enable operation of our GPU cloud services. We are enabling engineering teams to innovate while proactively identifying, tracking, and mitigating risks across the entire technical task. This role is ideal for engineers who thrive at the intersection of product, infrastructure, and software engineering and who want to build automated, intelligence-driven systems that protect NVIDIA's most critical AI platforms.

What you'll be doing: Telemetry Build and operate scalable telemetry pipelines for metrics, logs, traces, and events across on-premise, CSP, and NCP clusters. Establish common instrumentation, collection, storage, and access patterns so teams can generate and consume telemetry consistently. Deliver dashboards, alerting, and analysis capabilities that improve service visibility, detection, and troubleshooting.

Operational Excellence Standardize and automate incident, maintenance, service on-call, and support on-call workflows across HWInf. Integrate operational data and lifecycle signals to improve ownership, escalation, communication, and post-incident learning. Build reporting and AI-assisted tooling that reduces manual toil and improves operational responsiveness.

Cataloging and Inventory Build and maintain physical hardware and software catalogs as trusted sources of truth for infrastructure inventory, service ownership, dependencies, and documentation. Create consistent data models and integration pipelines that connect clusters, hardware, services, teams, and operational workflows. Provide self-service discovery capabilities so engineers can quickly identify what they operate, who owns it, and how to support it.

What we need to see: BS degree in Computer Science, Computer Engineering, or a related technical field, or equivalent experience. 8+ years of experience in infrastructure security, platform engineering, or security tooling. Proficiency in one or more programming languages such as Python, Go, Typescript, or Java.

Strong understanding of software and infrastructure principles, with experience applying them in production environments. Ability to lead cross-functional initiatives that span internal teams and external partners in varying disciplines across engineering, product, finance, and security. Ways to stand out from the crowd: Experience building and operating incident-management processes with internally built and/or externally vended SaaS tools Experience working with building, deploying, and maintaining ML models in production systems along with familiarity with AI agent frameworks or orchestration tools Experience building and operating modern observability platforms to deliver scalable metrics, logs, traces, and profiling Experience working with service catalog and configuration management databases (CMDB) NVIDIA is widely considered to be one of the technology world's most desirable employers.

We have some of the most forward-thinking and hard-working people in the world working for us. Are you creative and autonomous. Do you love a challenge.

If so, we want to hear from you. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.

If you're creative and self-motivated, we want to hear from you. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US