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Ai Infrastructure Jobs (NOW HIRING)

Analog Devices

Senior AI Infrastructure Engineer

Wilmington, MA · On-site

$118.60K - $161.30K/yr

Senior AI Infrastructure Engineer, Developer Experience Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the ...

vCluster Labs

AI Infrastructure Engineer

New York, NY · Remote

$150K - $200K/yr

As vCluster's AI Infrastructure Specialist, you will work directly with customers at the earliest and most critical stage of their journey: from bare metal GPU nodes through to a production-ready ...

Percepta

AI Infrastructure Engineer

New York, NY · On-site

$180K - $300K/yr

About the role We're hiring an AI Infrastructure Engineer to own the infrastructure, deployment, and operational reliability that powers Percepta's AI systems, including the autonomous agents at the ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100.90K - $132.40K/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 ...

Autonomous Solutions

AI Infrastructure Engineer IV

Mendon, UT · On-site

$93.70K - $122.90K/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 ...

Autonomous Solutions

AI Infrastructure Engineer IV

Mendon, UT · On-site

$93.70K - $122.90K/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 ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT

$100.90K - $132.40K/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 ...

Autonomous Solutions

AI Infrastructure Engineer IV

Mendon, UT · On-site

$93.70K - $122.90K/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 ...

Autonomous Solutions

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100.90K - $132.40K/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 ...

Data Direct Networks

CA

DDN is seeking a Client Director - Strategic AI Infrastructure to drive revenue growth in the U.S. West Coast region within our Artificial Intelligence business unit. This is a quota-carrying role ...

Data Direct Networks

CA

DDN is seeking a Client Director - Strategic AI Infrastructure to drive revenue growth in the U.S. West Coast region within our Artificial Intelligence business unit. This is a quota-carrying role ...

Seekr

Manager, AI Infrastructure

Austin, TX · On-site +1

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 ...

Data Direct Networks

CA

DDN is seeking a Client Director - Strategic AI Infrastructure to drive revenue growth in the U.S. West Coast region within our Artificial Intelligence business unit. This is a quota-carrying role ...

Data Direct Networks

CA · On-site

DDN is seeking a Client Director - Strategic AI Infrastructure to drive revenue growth in the U.S. West Coast region within our Artificial Intelligence business unit. This is a quota-carrying role ...

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How much do ai infrastructure jobs pay per hour?

As of May 29, 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 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 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 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.

More about Ai Infrastructure jobs
What cities are hiring for Ai Infrastructure jobs? Cities with the most Ai Infrastructure job openings:
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Ai Infrastructure jobs near you
Infographic showing various Ai Infrastructure job openings in the United States as of May 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $123,103 per year, or $59.2 per hour.
Senior AI Infrastructure Engineer

Senior AI Infrastructure Engineer

Analog Devices

Wilmington, MA • On-site

$118.60K - $161.30K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago

Analog Devices rating

8.5

Company rating: 8.5 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

21st of 137 rated electronics manufacturers

Job description

About Analog Devices
Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).
Senior AI Infrastructure Engineer, Developer Experience
Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).
This role is within the global Developer Experience (DevEx) team, specifically the Model Developer Experience (MDX) sub-team - whose mission is to deliver world-class infrastructure and platforms that enable AI builders across ADI to move faster, with confidence, and at scale. You will join a high-performance, mission-driven interdisciplinary team that spans data science, software engineering, platform architecture, cloud infrastructure, and security expertise. We believe in a culture founded on trust, mutual respect, growth mindsets, and an obsession for building extraordinary products with extraordinary people.
Role Summary
As a Senior AI Infrastructure Engineer (individual contributor), you will bring deep technical expertise in building scalable AI infrastructure across diverse deployment environments, and the ability to design elegant solutions that absorb operational complexity on behalf of AI builders across the organization. You will work embedded with data science and ML engineering teams to understand their infrastructure needs at the cutting edge, then translate those learnings into reusable, org-wide architectural patterns and platforms. You'll design and implement at critical infrastructure capabilities that span on-prem, hybrid, and cloud environments-from model serving and orchestration, to compute optimization, cost efficiency, and governance.
You will work at the intersection of research, technical architecture, and developer enablement-translating research and product goals into infrastructure systems that reduce complexity and accelerate innovation.
Key Responsibilities
AI Developer Experience
  • Partner directly with AI builder teams (data scientists, ML engineers, researchers) as an embedded technical advisor, understanding their infrastructure bottlenecks and platform needs at the point of creation.

  • Translate specific team engagements into generalizable patterns, standards, and architectural guidance that can be adopted across the organization.

  • Drive initiatives that reduce friction in the AI development lifecycle-from experimentation through production-by removing operational and technical barriers for builders.

  • Design and advocate for developer-friendly abstractions and APIs that hide infrastructure complexity while maintaining flexibility for advanced use cases.

  • Collaborate with cross-functional stakeholders to define what "excellent developer experience" means for AI infrastructure, then measure and iterate.

  • Contribute to org-wide standards for AI governance, model versioning, experiment tracking, and deployment workflows that balance flexibility with reliability.

On-Prem, Hybrid, and Cloud AI Infrastructure Engineering
  • Design and optimize AI infrastructure strategies that span heterogeneous environments-on-premise GPU clusters, hybrid cloud-edge deployments, and cloud-native architectures-ensuring seamless developer experience across all.

  • Architect compute orchestration and scheduling solutions (Kubernetes, Ray, or equivalent) that efficiently allocate resources across multiple environments and workload types.

  • Own infrastructure for model serving, inference optimization, and real-time inference pipelines supporting low-latency, edge-deployed AI models.

  • Define and implement cost optimization strategies across cloud and on-prem resources, including resource allocation, auto-scaling policies, and workload consolidation.

  • Build reusable Infrastructure-as-Code frameworks and tooling that other teams can adopt to provision and manage AI workloads consistently across environments.

  • Establish observability and monitoring strategies for AI infrastructure, including resource utilization, cost tracking, and performance metrics that enable proactive problem-solving.

  • Drive security and compliance standards for AI infrastructure, ensuring data residency, access control, and auditability across deployment environments.

  • Mentor engineers on infrastructure best practices, distributed systems concepts, and optimization techniques that improve platform reliability and developer productivity

Required Skills & Experience
  • Deep expertise in designing and operating AI infrastructure across multiple deployment paradigms (on-premises, hybrid, cloud-native).

  • Proven ability to work embedded with technical teams, understand complex requirements, and translate them into scalable architectural solutions.

  • Strong experience with Kubernetes, container orchestration, and distributed compute frameworks (Ray, Spark, or equivalent) at production scale.

  • Expert-level Infrastructure-as-Code proficiency (Terraform, CDK, or equivalent) with demonstrated ability to build reusable, multi-team infrastructure templates.

  • Deep knowledge of GPU/accelerator resource management, including scheduling, optimization, and cost tracking across heterogeneous hardware.

  • Experience designing model serving infrastructure and inference optimization pipelines for production AI workloads.

  • Strong understanding of modern cloud platforms (AWS, Azure, or equivalent) with hands-on experience building multi-cloud or hybrid strategies.

  • Demonstrated ability to solve complex infrastructure problems through systematic analysis and creative engineering.

  • Strong communication skills and ability to translate technical concepts for both engineering and non-technical audiences.

  • Mentoring orientation with demonstrated success upskilling engineers on infrastructure and platform topics.

Preferred Skills - Physical Intelligence and Industrial AI
  • Experience building or scaling AI infrastructure for robotics, autonomous systems, or industrial perception applications.

  • Familiarity with ROS/ROS2 ecosystems and the infrastructure challenges of deploying ML models in robotic systems.

  • Background in edge AI deployment, including optimization for low-latency inference on resource-constrained devices.

  • Experience designing ML infrastructure that supports rapid iteration and few-shot adaptation in physical systems.

  • Knowledge of heterogeneous compute architectures combining CPUs, GPUs, and specialized processors (NPUs, FPGAs, etc.).

  • Experience with real-time operating systems or hard real-time constraints in distributed systems.

  • Understanding of manufacturing, autonomous vehicle, or healthcare domains and their infrastructure requirements for AI applications.

For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position - except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) - may have to go through an export licensing review process.
Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.
EEO is the Law: Notice of Applicant Rights Under the Law.
Job Req Type: Experienced
Required Travel: Yes, 10% of the time
Shift Type: 1st Shift/Days
The expected wage range for a new hire into this position is $144,000 to $198,000.
  • Actual wage offered may vary depending on work location, experience, education, training, external market data, internal pay equity, or other bona fide factors.
  • This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.
  • This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.

What Analog Devices employees say

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Hours and flexibility

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About Analog Devices

Sourced by ZipRecruiter

Analog Devices (NASDAQ: ADI) designs and manufactures semiconductor products and solutions. We enable our customers to interpret the world around us by intelligently bridging the physical and digital worlds with unmatched technologies that sense, measure and connect.

Industry

Electrical equipment, appliance, and component manufacturing

Company size

5,001 - 10,000 Employees

Headquarters location

Norwood, MA, US

Year founded

1965

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