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Ai Devops Engineer Jobs in Arizona (NOW HIRING)

Triumph Tech, LLC

Be Seen First

DevOps Engineer

Phoenix, AZ · On-site

$100K - $120K/yr

Have experience with CI/CD tools (Azure DevOps Pipelines, GitHub Actions, or similar) * Are familiar with packaging and deployment (NuGet, MSBuild, or installer/package creation for on-prem software ...

Triumph Tech, LLC

Be Seen First

Devops Engineer

Phoenix, AZ · On-site

$100K - $120K/yr

Have experience with CI/CD tools (Azure DevOps Pipelines, GitHub Actions, or similar) * Are familiar with packaging and deployment (NuGet, MSBuild, or installer/package creation for on-prem software ...

ClifyX

AWS & Azure Devops Engineer

Chandler, AZ · On-site

$53.75 - $73.75/hr

AWS & Azure Devops Engineer Location: Chandler, AZ (Onsite) Type: Full-time Must Have Technical/Functional Skills Primary Skill: AWS & Azure Devops Engineer Secondary: Terraform, Ansible, Python ...

BloKchain Talent

Audio Conference DevOps Engineer

Tempe, AZ · On-site

$51.25 - $70.25/hr

Audio Conference DevOps Engineer LOCATION : Phoenix AZ SALARY : Based on Experience SPONSORSHIP : No We're looking for a Audio Conference DevOps Engineer to manage the deployment of new release ...

BloKchain Talent

Audio Conference DevOps Engineer

Tempe, AZ · On-site

$51.25 - $70.25/hr

Audio Conference DevOps Engineer LOCATION : Phoenix AZ SALARY : Based on Experience SPONSORSHIP : No We're looking for a Audio Conference DevOps Engineer to manage the deployment of new release ...

QTS Data Centers

Senior DevOps Engineer-1

Phoenix, AZ · On-site

$129K - $165K/yr

QTS Data Centers is a leading provider of data center services, and they are seeking a Senior DevOps Engineer to manage the configuration, deployment, and maintenance of their Services Delivery ...

Ghr

Senior DevOps Engineer

Chandler, AZ · On-site

$128K - $164K/yr

Mentors DevOps Engineers while setting/contributing to their technical skills development roadmaps, responding to impactful events or issues, and communicating action-plan to * Responds to complex ...

New

ClifyX

AWS & Azure Devops Engineer

Chandler, AZ · On-site

$51.75 - $71/hr

ClifyX is a company seeking an AWS & Azure Devops Engineer to assist in designing and deploying CTI Platform service designs and AWS Azure database services. The role involves facilitating the ...

BloKchain Talent

Senior DevOps Engineer

Tempe, AZ · On-site

$126K - $162K/yr

Senior DevOps Engineer LOCATION : Phoenix AZ SALARY : Based on Experience SPONSORSHIP : No Responsibilities * Design and implement zero-downtime to accomplish highly available service (99.999%

BloKchain Talent

Senior DevOps Engineer

Tempe, AZ · On-site

$126K - $162K/yr

Senior DevOps Engineer LOCATION : Phoenix AZ SALARY : Based on Experience SPONSORSHIP : No Responsibilities * Design and implement zero-downtime to accomplish highly available service (99.999%

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Showing results 21-40

All JobsAi Devops Engineer JobsAi Devops Engineer Jobs in Arizona

Ai Devops Engineer information

See Arizona salary details

$15

$56

$80

How much do ai devops engineer jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for ai devops engineer in Arizona is $56.41, according to ZipRecruiter salary data. Most workers in this role earn between $47.26 and $64.76 per hour, depending on experience, location, and employer.

What is an AI DevOps engineer?

AI DevOps Engineers are professionals who blend expertise in artificial intelligence (AI) and DevOps practices to streamline the development, deployment, and maintenance of AI-powered applications. They automate and manage the continuous integration and continuous deployment (CI/CD) pipelines for machine learning models, ensuring scalability, reliability, and efficiency in production environments. Their role also includes monitoring AI systems, managing model versions, and collaborating with data scientists, software engineers, and IT teams to bridge the gap between development and operations. This position is crucial for organizations looking to operationalize AI solutions at scale.

What are the key skills and qualifications needed to thrive as an AI DevOps engineer?

To thrive as an AI DevOps Engineer, you need expertise in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD systems, version control (e.g., Git), and cloud platforms (AWS, Azure, GCP), as well as certifications such as AWS Certified DevOps Engineer, are highly valuable. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and adapt to evolving project requirements. These competencies are essential to ensure robust, scalable, and efficient deployment of AI solutions in production environments.

How does an AI DevOps engineer typically collaborate with data scientists and software engineers on AI projects?

An AI DevOps Engineer plays a crucial role in bridging the gap between data scientists and software engineers by streamlining the deployment and monitoring of AI models. They often work closely with data scientists to automate model training, testing, and deployment pipelines, ensuring that models move smoothly from development to production. Additionally, they collaborate with software engineers to integrate models into scalable applications, manage infrastructure, and set up monitoring systems to track performance and reliability. This role requires strong communication skills and a proactive approach to troubleshooting issues that arise in cross-functional teams.

What is the difference between Ai Devops Engineer vs Data Engineer?

AspectAi Devops EngineerData Engineer
Required CredentialsCertifications in cloud platforms, DevOps tools, AI/ML frameworksCertifications in data management, SQL, cloud platforms
Work EnvironmentCollaborates with AI/ML teams, DevOps, cloud infrastructureWorks with data pipelines, databases, big data tools
Employer & Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, e-commerce, data-driven industries

Ai Devops Engineers focus on deploying and maintaining AI/ML models in production using DevOps practices, while Data Engineers build and manage data pipelines and infrastructure. Both roles require cloud and scripting skills but serve different stages of data and AI workflows.

Will AI take AI Devops Engineer jobs?

AI DevOps Engineers focus on integrating AI models into deployment pipelines, automating infrastructure, and managing AI systems. While AI tools can automate certain tasks, the role requires expertise in both AI and DevOps practices, making complete automation unlikely in the near term. Human oversight remains essential for designing, maintaining, and improving AI deployment processes.

What are popular job titles related to Ai Devops Engineer jobs in Arizona?

For Ai Devops Engineer jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Ai Devops Engineer jobs in Arizona look for?

The top searched job categories for Ai Devops Engineer jobs in Arizona are:

What cities in Arizona are hiring for Ai Devops Engineer jobs?

Cities in Arizona with the most Ai Devops Engineer job openings:

Ai Devops Engineer jobs near you
Infographic showing various Ai Devops Engineer job openings in Arizona as of August 2026, with employment types broken down into 78% Full Time, 18% Part Time, 2% Temporary, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $117,332 per year, or $56.4 per hour.

DevOps Engineer / Kubernetes Engineer

Northern Base

Phoenix, AZ • On-site

$52.50 - $71.75/hr

Full-time

Posted 20 days ago

Job description

Hiring Alert | DevOps Engineer / Kubernetes Engineer

Location: Phoenix, AZ (Onsite)
Employment Type: Full-Time
Visa Type: USC / GC Only
Experience: 6+ Years

Top Must-Have Skills
  • Kubernetes – Cluster administration & troubleshooting
  • OpenShift or similar Kubernetes platforms in Public Cloud
  • Observability – Strong hands-on experience
  • Prometheus & Grafana
  • Splunk
  • Container runtime management
  • Terraform / Helm / Ansible / GitOps
Required Skills
  • 6+ years of experience in DevOps / Kubernetes Engineering
  • Strong hands-on experience with Kubernetes cluster administration and troubleshooting
  • Hands-on experience with OpenShift or equivalent Kubernetes platforms
  • Strong knowledge of Prometheus, Grafana, Alertmanager, and Splunk
  • Experience with ELK/OpenSearch or similar log aggregation platforms
  • Knowledge of Kubernetes networking, including Ingress, Services, and CNI plugins
  • Experience with container runtimes
  • Hands-on experience with Terraform, Helm, or Ansible
  • Experience with GitOps tools such as Argo CD or Flux
  • Knowledge of distributed tracing, metrics collection, and log aggregation
  • Exposure to service mesh technologies such as Istio or Linkerd is a plus
  • Strong troubleshooting, reliability, and problem-solving skills
  • Ability to drive and promote strong engineering practices
Key Responsibilities
  • Administer, troubleshoot, and maintain Kubernetes clusters.
  • Perform OpenShift administration or work with equivalent Kubernetes platforms.
  • Manage container runtimes and Kubernetes environments.
  • Implement and maintain observability solutions using Prometheus, Grafana, Alertmanager, Splunk, ELK/OpenSearch, or similar tools.
  • Handle log aggregation, metrics collection, and distributed tracing.
  • Work with Kubernetes networking concepts including Ingress, Services, CNI plugins, and service mesh technologies such as Istio/Linkerd.
  • Automate infrastructure using Terraform, Helm, Ansible, and GitOps tools such as Argo CD or Flux.
  • Drive and promote strong engineering practices focused on reliability, quality, and operational excellence.
  • Collaborate with and coach engineering teams to build highly reliable applications.
Ideal Candidate

A senior Kubernetes/DevOps Engineer with strong hands-on experience in Kubernetes, OpenShift, Prometheus, Grafana, Splunk, observability, infrastructure automation, and Kubernetes networking, with a strong focus on reliability, troubleshooting, and engineering best practices.