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Ai Infrastructure Jobs (NOW HIRING)

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

As an AI Infrastructure Engineer IV, you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our compute ...

Seekr

Manager, AI Infrastructure

Austin, TX · On-site

We are seeking an Infrastructure Manager with deep expertise in Kubernetes, Terraform, and Ansible to help scale Seekr's AI platform across on-premises, cloud, and SaaS environments. You'll be highly ...

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$126K - $165K/yr

* Design, build, and operate on-prem infrastructure that behaves like a cloud environment for internal teams, including AI/ML workloads * Own datacenter and infrastructure operations: compute, storage ...

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$126K - $165K/yr

* Design, build, and operate on-prem infrastructure that behaves like a cloud environment for internal teams, including AI/ML workloads * Own datacenter and infrastructure operations: compute, storage ...

Scout Motors

AI Infrastructure Engineer

Charlotte, NC · On-site

$105K - $137K/yr

Install, configure, and maintain AI platform and tools. * Design, deploy, and operate infrastructure supporting ML and LLM workloads. * Build, containerize, and deploy AI services using Docker.

Accenture

AI & HPC Infrastructure Engineer

Saint Louis, MO · On-site

$97K - $127K/yr

The Global AI Infrastructure team is at the center of enabling infrastructure reinvention for the next era of digital solutions powered by AI, accelerated computing, and high-performance workloads.

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$117K - $154K/yr

* Design, build, and operate on-prem infrastructure that behaves like a cloud environment for internal teams, including AI/ML workloads * Own datacenter and infrastructure operations: compute, storage ...

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Ai Infrastructure information

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How much do ai infrastructure jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for ai infrastructure in the United States is $59.18, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $68.99 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 may earn higher salaries, often exceeding $180,000.

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?

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 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.
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Ai Infrastructure jobs near you
Infographic showing various Ai Infrastructure job openings in the United States as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $123,103 per year, or $59.2 per hour.

AI Infrastructure Engineer IV

Autonomous Solutions

Lehi, UT • On-site

$100K - $132K/yr

Full-time

Re-posted 5 days ago

Job description

At ASI, we are revolutionizing industries with state-of-the-art autonomous robotics solutions. Within the fields of agriculture, construction, landscaping, and logistics, we deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail and Growth guiding everything we do, we're shaping the future of automation in dynamic markets. As an AI Infrastructure Engineer IV, you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our compute, storage, and cloud environments are scalable, efficient, and tuned for high-performance AI workloads. Working closely with data scientists, robotics engineers, and software teams, you'll develop robust infrastructure that supports the deployment and reliability of our AI-driven autonomous systems. Responsibilities:Design, build, and maintain high-performance computing infrastructure including CPUs, GPUs, storage, and networking to support AI and ML workloads.Deploy and manage AI systems within cloud environments (AWS, Azure, GCP), ensuring scalability, cost-efficiency, and high availability.Collaborate with data scientists, ML engineers, and software teams to support AI model development, training, and deployment workflows.Implement automation, CI/CD, DevOps, and MLOps practices to create efficient, repeatable, and reliable AI infrastructure processes.Optimize compute and storage systems to achieve maximum performance and throughput for AI/ML pipelines.Monitor system health and troubleshoot performance bottlenecks, infrastructure issues, and deployment challenges. Required Qualifications:Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.8+ years of experience in cloud infrastructure, DevOps, or platform engineering with 3+ years working on AI/ML systems.Strong understanding of modern AI infrastructure components, including distributed computing, GPU-accelerated systems, and large-scale storage.Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.Proficiency with Kubernetes, Docker, Terraform, or similar containerization and orchestration tools.Strong programming skills in Python and/or C++, with experience supporting machine learning frameworks (TensorFlow, PyTorch, etc.).Experience implementing CI/CD pipelines, MLOps practices, and automation tooling. At Autonomous Solutions, Inc. (ASI), we are committed to fostering a diverse, inclusive, and equitable workplace where all employees and applicants have equal opportunities. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other legally protected characteristic. ASI complies with all applicable federal, state, and local laws regarding non-discrimination in employment and is dedicated to providing reasonable accommodations for individuals with disabilities throughout the hiring process.
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