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Ai Infrastructure Jobs in Raleigh, NC (NOW HIRING)

Bandwidth

Applied AI Engineer

Raleigh, NC · On-site

$104K - $137K/yr

This is an infrastructure and systems role with a deep AI focus. What You'll Do: * Own and extend existing AI platforms and tooling, improving reliability, expanding capabilities, and integrating ...

Ccube

AI & ML Tech Lead/Architect

Durham, NC · On-site

$150K - $225K/yr

Exposure to MCP, A2A, or similar AI infrastructure concepts. Experience with containerization (Docker, Kubernetes) and CI/CD pipelines. Knowledge of data pipelines and AI model lifecycle management ...

CCube Solutions

AI & ML Tech Lead/Architect

Raleigh, NC · On-site

$150K - $225K/yr

Exposure to MCP, A2A, or similar AI infrastructure concepts. Experience with containerization (Docker, Kubernetes) and CI/CD pipelines. Knowledge of data pipelines and AI model lifecycle management ...

Berriehill Research

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 ...

Berriehill Research

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 ...

ARA

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 ...

Bandwidth

Sr. Software Developer (Infrastructure)

Raleigh, NC · On-site

$53 - $70/hr

Design and operate Bandwidth's AI infrastructure layer, including our LLM gateway, model routing, and cost controls, so every engineering team can experiment with AI tools safely and cheaply. * Build ...

Cherry Bekaert

AI Architect

Raleigh, NC · On-site

$61.25 - $80.75/hr

Develops integration patterns connecting AI capabilities with the Firm's enterprise systems, collaboration platforms, document management tools and data infrastructure. * Creates and curates service ...

Epic Games

Principal Engineer, AI Platform

Cary, NC · On-site

$125K - $167K/yr

ONLINE INFRASTRUCTURE What We Do We enable Epic's online services teams to build, deploy, and ... AI Agent Orchestration - multi-tenant platform for team AI agents that live and collaborate in ...

Deloitte

Senior AI Engineer - SFL Scientific

Raleigh, NC · On-site

$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

Principal Product Manager

Morrisville, NC

You will sit at the intersection of enterprise storage, Azure AI infrastructure, and industry AI workloads, ensuring ANF is positioned and built as a strategic data foundation for training, inference ...

NetApp

Principal Product Manager

Morrisville, NC

You will sit at the intersection ofenterprise storage,Azure AI infrastructure, andindustry AI workloads, ensuring ANF is positioned and built as astrategic data foundationfor training, inference, RAG ...

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Ai Infrastructure information

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How much do ai infrastructure jobs pay per hour?

As of Jul 3, 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 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.

How much do AI infrastructure engineers make?

AI infrastructure engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and hardware optimization can earn higher salaries, often exceeding $180,000 per year.

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 the key skills and qualifications needed to thrive in AI Infrastructure, and why are they important?

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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI architect, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses that contribute to the high total compensation.

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 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 engineer makes $500,000 a year?

Senior AI infrastructure engineers or machine learning engineers with extensive experience, specialized skills, and advanced certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. These roles often require expertise in cloud platforms, distributed systems, and deep learning frameworks, along with leadership responsibilities and a strong track record of impactful projects.
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 June 2026, with employment types broken down into 70% Full Time, 28% Part Time, and 2% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $119,666 per year, or $57.5 per hour.

Senior/Staff AI Engineer

Data Direct Networks

Raleigh, NC

$150K - $250K/yr

Full-time

Posted 20 days ago

Job description

Overview

Build the AI infrastructure layer that determines whether modern models actually work in production.

Most AI roles sit at the application layer. This one does not.

At DDN, we're hiring an AI Engineer to work on the hard part of AI: the systems, storage, and performance infrastructure behind real-world model serving and inference. This is the role for engineers who care about what happens under load, at scale, and in production - not just in demos.

If your background sits at the intersection of AI infrastructure, distributed systems, and performance engineering, this is the kind of role where your depth will matter.

Job Description

What you'll do

  • Build and optimize LLM serving and inference systems for production environments
  • Improve performance across GPU and CPU pathways
  • Work on KV cache, memory, storage, and throughput bottlenecks
  • Design and scale systems that support RAG and retrieval-heavy AI workloads
  • Contribute to infrastructure where storage architecture and systems efficiency materially affect AI performance
  • Solve engineering problems at the intersection of AI, high-performance systems, and distributed infrastructure

What we're looking for

  • An engineer who has spent meaningful time building or optimizing production AI systems, not just experimenting with models
  • Someone who understands how inference performance is shaped by the interaction between compute, memory, storage, and serving architecture
  • Deep hands-on experience working close to the systems layer - for example, improving how workloads run across GPU and CPU resources, reducing bottlenecks, or tuning infrastructure for better throughput and latency
  • Evidence of real ownership in areas like model serving, retrieval, caching, storage, or distributed performance, rather than purely application-layer AI work
  • The ability to move comfortably between architecture decisions and hands-on implementation, especially in environments where efficiency and scale matter
  • A background that suggests you can operate in technically demanding environments, whether that comes from AI infrastructure, high-performance systems, storage platforms, or adjacent distributed systems work
  • PhD preferred, but far less important than having built serious systems in the real world

Why this role is compelling

  • This is not a "prompt engineering" job.
  • This is not an "AI wrapper" job.
  • This is not a generic backend role with AI sprinkled on top.
  • This is a chance to work on the infrastructure that determines whether modern AI systems are fast, scalable, efficient, and commercially viable.
  • If you want to work on the real mechanics of AI performance - serving, retrieval, compute efficiency, memory behavior, storage architecture, and inference at scale - this is where that work happens.

Who will love this role

  • Engineers who enjoy deep systems problems
  • Builders who care about performance, scale, and architecture
  • People who want to work where AI meets infrastructure
  • Candidates who would rather solve hard technical bottlenecks than ship surface-level AI features

Who should not apply

This role is not for:

  • Purely academic researchers without meaningful production ownership
  • Generic software engineers without clear AI systems or inference depth
  • Candidates focused mainly on prompt engineering or lightweight application integrations
  • MLOps generalists who have not worked deeply on serving, storage, or performance-critical AI systems

Salary Range: $150,000 - $250,000

DDN

Why DDN - DDN has deep credibility in high-performance infrastructure, and this role sits in a part of the market where that foundation matters. If you want to build the systems serious AI depends on - rather than the layer that merely sits on top of it - this is a rare opportunity to do exactly that.

Apply if you want to build the infrastructure behind production AI - not just consume it.

#Linkedin

Employment Type: FULL_TIME

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