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Ai Infrastructure Jobs in Raleigh, NC (NOW HIRING)

Nvidia

Senior Applied AI Engineer

Durham, NC · On-site

$101K - $138K/yr

Design, develop, and improve scalable infrastructure to support the next generation of AI ... applications, including copilots and agentic tools. * Drive improvements in architecture ...

Nvidia

Senior Applied AI Engineer

Durham, NC · On-site

$118K - $156K/yr

Design, develop, and improve scalable infrastructure to support the next generation of AI ... applications, including copilots and agentic tools. Drive improvements in architecture, performance ...

Deloitte

Senior AI Engineer - SFL Scientific

Raleigh, NC

$101K - $139K/yr

Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns * Define and lead technology proof of concepts to ensure feasibility of new data and cloud ...

NetApp

Sr. Technical Marketing Engineer

Morrisville, NC · On-site +1

$196K/yr

Job Summary The CI Solutions team builds, validates, and launches NetApp data management, hybrid cloud, FlexPod, and next-generation AI infrastructure solutions. This role serves as a technical ...

VAST Data

Forward Deployed Engineer

Raleigh, NC · On-site +1

Description VAST Data is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make ...

Actalent

Operational Manager

Morrisville, NC · On-site

$100K - $188K/yr

Support new product introductions (NPI), product launches, manufacturing readiness, and scalability initiatives for AI, HPC, cloud, and enterprise infrastructure products. * Manage operating budgets ...

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Ai Infrastructure information

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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:

Ai Infrastructure jobs near you
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 Software Engineer, System Validation - EDA Infrastructure

Nvidia

Durham, NC • On-site

$104K - $142K/yr

Full-time

Posted 20 days ago

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

NVIDIA is hiring engineers to scale up the introduction of next generation architecture into its EDA Infrastructure. We expect you to have a deep understanding of new product introductions (NPIs), distributed systems, familiarity with software testing and deployment, and excellent communication and planning abilities. We also welcome out-of-the-box thinkers who can provide new ideas with strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You and other engineers in this team will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions. What are you waiting for if you're creative, passionate about what you do, and love having fun apply today!

We're looking for a highly motivated, creative candidate with strong experience in new product introductions at scale to join the EDA Team. Principal Software Engineer available for suitable candidates. You will lead the architecture, design and implementation of our EDA clusters using the latest technologies. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement.

What you'll be doing:

  • Lead technical activities for new product introductions at scale with focus on hybrid deployments between cloud and on-prem

  • Providing expertise in new product introduction planning spanning infrastructure workflows, hardware, software release, workload orchestration and application tuning

  • Provide fast and creative solutions for complex problems and write effective, clear and reliable architecture specification

  • Translate requirements to vision, architecture and roadmap

  • Work with engineering teams across NVIDIA to ensure new product architectures integrate seamlessly from the hardware all the way up to workloads.

What we need to see:

  • 12+ overall years of experience

  • BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience.

  • A proven track record of impactful project deliveries focused on cloud infrastructure or cloud application services.

  • Experience with at scale infrastructure, DevOps and/or SRE practices and/or Platform Engineering.

  • Systematic problem-solving approach, coupled with strong communications skills and a sense of ownership and drive.

  • System-level experience with both hardware and software

  • Motivated self-starter with an equal balance of strong problem-solving skills and customer-facing communication skills

  • Passion for continuous learning and knowledge transfer. Ability to work concurrently with multiple groups locally and abroad in the organization

Ways to stand out from the crowd:

  • Developing ML/AI infrastructure. Developing bare metal as a service (BMaaS) associated systems. Developing multi-cloud infrastructure services.

  • Interest in crafting, analyzing and fixing large-scale distributed systems.

  • Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is seeking exceptional individuals like you to help us drive the next wave of artificial intelligence.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 3, 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

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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

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