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Ai Infrastructure Jobs in Raleigh, NC (NOW HIRING)

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 ...

Western Governors University

Staff AI Engineer

Raleigh, NC · On-site +1

$180K - $279K/yr

Drive build-vs-buy and vendor evaluation decisions for AI frameworks, models, and infrastructure * Design and scale internal AI platforms including shared tooling, reusable components, prompt ...

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 ...

Ammortal Inc

AI Solutions Lead

Raleigh, NC · On-site +1

$100K - $125K/yr

You work on internal systems, infrastructure and the Chamber. Your work touches all departments and ... AI Implementation - Design, build, and maintain all of our AI systems across the company.

Nvidia

Senior Applied AI Engineer

Durham, NC

$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 ...

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

Principal Product Manager

Morrisville, NC · On-site

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 ...

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Ai Infrastructure information

See Raleigh, NC salary details

$27

$57

$84

How much do ai infrastructure jobs pay per hour?

As of Jul 31, 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 July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution, with an average salary of $119,660 per year, or $57.5 per hour.

Senior Platform Engineer, Data & AI Infrastructure

McKinney

Durham, NC • On-site

$104K - $142K/yr

Full-time

Re-posted 28 days ago

Job description

Purpose
We're looking for a DevOps / Cloud Security / Data Infrastructure Engineer who will build, operate, and evolve the cloud infrastructure and data platform that powers McKinney's internal AI and analytics products. You'll own the foundation that enables our data lakehouse - managing pipelines, orchestration, infrastructure-as-code, and platform reliability so that our engineering and data teams can ship fast and with confidence.
You'll work alongside our Applied Emerging Technology (AET) department to operate a modern stack built on AWS, Snowflake, Fivetran, DBT, FastAPI, and Okta (auth0). You'll be hands-on with infrastructure automation, CI/CD, observability, and data pipeline health - from early design through deployment, monitoring, and iteration.
Ideal Candidate
  • You think in systems: pipelines, infrastructure state, observability, and failure modes are your natural vocabulary.
  • You're comfortable owning cloud infrastructure end-to-end, from provisioning to incident response.
  • You have a strong data engineering sensibility. You understand ELT patterns, warehouse architecture, and what makes pipelines reliable and cost-efficient.
  • You automate everything, write infrastructure as code, and treat configuration drift as a bug.
  • You collaborate closely with software engineers, data analysts, and product owners.
  • You're curious about AI infrastructure and excited to support LLM-powered products in production.
  • You have used and are learning to leverage AI-coding assistants ( codex, claude-code, etc. )
  • Networking / cloud security experience

Responsibilities
  • Design, build, and maintain cloud infrastructure on AWS using Terraform and GitOps (or comparable) workflows; manage environments (dev, staging, production) with consistency and auditability.
  • Own and operate Snowflake data warehouse infrastructure: virtual warehouse sizing and cost governance, resource monitors, account-level configurations, and integration with Fivetran and/or DBT.
  • Manage and monitor ELT connectors; troubleshoot sync failures, schema drift, and performance issues; coordinate with source system owners on connector changes.
  • Support and extend pipelines: manage job scheduling, run monitoring, model dependencies, and test coverage; work with data practitioners on performance optimization.
  • Operate and harden our dev platform: manage user access, environment variables, secrets, deployment configurations, and platform upgrades.
  • Administer Okta SSO integrations and auth0 across the platform; manage application assignments, SCIM provisioning, and authentication policies.
  • Build and maintain CI/CD pipelines for infrastructure and application code; enforce automated testing, security scanning, and deployment gates.
  • Author and maintain Dockerfiles and container images; manage image lifecycle in a container registry; enforce container security best practices.
  • Establish and maintain observability across the stack: metrics, logs, traces, and alerting for pipelines, APIs, and platform services.
  • Manage secrets, IAM roles, and least-privilege access policies across AWS services; maintain a strong security and compliance posture.
  • Perform capacity planning, cost optimization, and FinOps hygiene across AWS and Snowflake; report on platform spend and efficiency.
  • Document infrastructure architecture, runbooks, and incident postmortems; contribute to disaster recovery and business continuity planning.

Qualifications
Professional Skills
  • AWS: Strong hands-on experience with core services (EC2, ECS/Fargate, Lambda, RDS, S3, IAM, VPC, CloudWatch, Secrets Manager, ECR, CodeBuild/CodePipeline); experience with cost optimization and tagging strategies.
  • Infrastructure as Code: Terraform (required); GitOps or comparable workflows; experience managing multi-environment infrastructure with state management and module reuse.
  • Snowflake Administration: Virtual warehouse management, resource monitors, role-based access control, data sharing, and cost governance; familiarity with Snowflake architecture (micro-partitions, clustering, caching).
  • Data Pipeline Operations: Hands-on experience operating ELT pipelines (Fivetran or comparable); understanding of connector types, sync modes, and failure recovery patterns.
  • DBT: Experience running and monitoring DBT Cloud or Core jobs; understanding of model dependencies, incremental strategies, and test frameworks.
  • CI/CD: GitHub Actions or equivalent; automated build, test, and deployment pipelines for both application and infrastructure code.
  • Containers: Docker image authoring (multi-stage builds), image scanning, registry management; ECS/Fargate deployment experience.
  • Observability: Experience implementing metrics, logging, and alerting stacks (CloudWatch, Datadog, or comparable); on-call participation and incident response.
  • Security & Identity: IAM least-privilege design, Okta SSO/auth0 administration, secrets management, and security best practices for cloud-native environments.
  • Scripting: Python or comparable for automation, tooling, and operational tasks.

Competencies
  • Communicates clearly with engineering, data, and product partners; translates infrastructure concerns into business-relevant language.
  • Ownership and accountability; follows through on incidents, changes, and documentation.
  • Reliability-first mindset balanced with a pragmatic approach to speed and iteration.
  • Growth mindset; stays current with cloud and data tooling developments.
  • Uses AI assistants responsibly to accelerate infrastructure work, with critical validation of generated configurations and scripts.

Experience
  • 5+ years of professional DevOps, Platform Engineering, or Data Infrastructure experience.
  • Proven hands-on experience with AWS and Terraform in production environments.
  • Demonstrable experience operating a modern data stack (Snowflake, Fivetran, or DBT in any combination).
  • Experience with container-based deployments and CI/CD automation.
  • Prior work in a small, high-ownership team where you wore multiple infrastructure hats is a strong plus.

Salary Range
Our estimated range for this role is $130-$150k
Compensation packages are based on the skill level and experience each candidate brings to their role. There may also be a more senior or junior position available that could be a better fit with your expertise. Each level has its own compensation range.
We pride ourselves on competitive salaries, and ensuring pay equity exists across our organization. We benchmark each position against existing employee competencies and 4As compensation data which includes geographic and agency size benchmarks. We also meet with department leaders 3x/year to ensure we are supporting employees in living into their full potential. Our promotions are not limited to a specific time per year. Promotions are tied to performance.
Right To Work In The US
You must be authorized to work in the US for any employer. At this time, we are not sponsoring or providing assistance with obtaining work authorization.
McKinney is a place where everyone can grow. Studies have shown that marginalized communities such as women, LGBTQ+ and people of color are less likely to apply to jobs unless they meet every single qualification. However you identify, and whatever background you bring with you, please apply if this is a role that would make you excited to come into work every day.
We are in the office Tuesday/Wednesday/Thursday on a hybrid schedule. We look forward to meeting you!
About McKinney
McKinney is a creative agency that gets unfair attention for brands. In 2024, McKinney was named to Fast Company's Best Workplaces for Innovators list, as well as Ad Age's A-List and its list of Best Places to Work (2024 and 2025), reinforcing the agency's commitment to providing an exceptional workplace culture where employees thrive, and creativity flourishes. McKinney Health, the agency's Pharma and Wellness practice, launched in 2022, was named to MM+M Magazine's 2024 Agency 100 list. A Certified B Corporation, McKinney is part of the Cheil Worldwide network and has offices across the country, including Durham, New York, Los Angeles, Dallas, Phoenix, and Toronto. McKinney has been recognized by Cannes Lions, Effies, The One Show, D&AD, ANDY, CLIO, LIA, the Shortys, and The Webby Awards, among others. Client partners include brands such as Popeyes, Blue Diamond Growers, Little Caesars, Pampers, Henkel, Samsung, Indivior, Sherwin-Williams, Biogen and the Ad Council. For more information, visit mckinney.com.

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