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Ai Devops Engineer Jobs in Dallas, TX (NOW HIRING)

DevOps Engineer

Dallas, TX ยท On-site

$52.25 - $71.50/hr

Position Overview We are seeking a highly skilled Mid-Level to Senior DevOps Engineer with hands-on ... AI / MLOps / AIOps * Deploy, manage, and optimize AI/ML workloads in production environments.

DevOps Engineer - Remote

Dallas, TX ยท Remote

$50 - $150/hr

No prior AI experience is required--your DevOps expertise and engineering judgment are what matter most. Key Responsibilities * Design realistic DevOps tasks covering CI/CD, containers, Kubernetes ...

New

Aws DevOps Engineer

Dallas, TX ยท On-site

$52.50 - $71.75/hr

AWS Devops Engineer Location: Chicago, IL and Dallas, TX Experience: 10+ years Role and Overview of ... AI/ML Ops with SageMaker & Bedrock Education and Experience * 5-7 years of software development ...

Senior DevOps Engineer

Dallas, TX ยท On-site

$128K - $165K/yr

Position Overview We are seeking a highly skilled Mid-Level to Senior DevOps Engineer with hands-on ... AI / MLOps / AIOps * Deploy, manage, and optimize AI/ML workloads in production environments.

Lead Azure DevOps Engineer

Frisco, TX ยท On-site

$49.25 - $67.50/hr

... AI, engineering, and other emerging technologies. Key Responsibilities * Lead Azure DevOps and cloud initiatives for AD. * Work closely with client and delivery teams to design, implement, and ...

DevOps Engineer

Dallas, TX ยท On-site

$48.75 - $66.75/hr

Position Title * DevOps Engineer ACSXAG85 Position Responsibilities DevOps Engineer Plano TX (Hybrid role) Visa Open (W2 Candidates) Must have skill: Ansible, DevOps Specialist, DevOps Qualifications:

DevOps Engineer

Dallas, TX

$52.25 - $71.50/hr

Job Advertisement - DevOps Engineer Company Overview: We are a fastgrowing technology company focused on delivering reliable, scalable, and secure cloudnative applications to enterprise clients. Our ...

DevOps Engineer

Dallas, TX ยท On-site

$52.25 - $71.50/hr

Job Advertisement - DevOps Engineer Company Overview: We are a fast-growing technology company focused on delivering reliable, scalable, and secure cloud-native applications to enterprise clients.

Devops Engineer

Richardson, TX ยท On-site

$48 - $65.50/hr

Python Scripting * Kubernetes * DevOps (CI/CD) * Terraform (Infrastructure as Code) * Cloud ... AI/ML Platform exposure Experience: 6+ Years (Preferred)

DevOps Engineer

Plano, TX ยท On-site

$110 - $150/hr

Job Title: DevOps Engineer Location: Plano, TX (Hybrid -- 3 days/week onsite; only local candidates will be considered) Company Overview Our client is a leading multinational telecommunications ...

DevOps Engineer

Westlake, TX ยท On-site

$65 - $70/hr

On-site Every Other Week onsite / 5 days in either Westlake, TX or Merrimack, NH As a DevOps team ... All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring ...

DevOps Engineer

Dallas, TX ยท On-site

$52.25 - $71.50/hr

TITLE : DEVOPS ENGINEER LOCATION : DALLAS, TX Work with the Sr DevOps engineer to implement the DevOps, CI/CD function Work with the Sr DevOps engineer to identifying the tool set for, designing and ...

DevOps Engineer

Addison, TX ยท On-site

$51 - $70/hr

As a DevOps Engineer, you will be a key contributor to the development and operations lifecycle, owning the endtoend automation of infrastructure provisioning, CI/CD pipelines, deployments ...

DevOps Engineer

Addison, TX ยท On-site

$51 - $70/hr

As a DevOps Engineer, you will be a key contributor to the development and operations lifecycle, owning the end-to-end automation of infrastructure provisioning, CI/CD pipelines, deployments ...

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Ai Devops Engineer information

See Dallas, TX salary details

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How much do ai devops engineer jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for ai devops engineer in Dallas, TX is $59.88, according to ZipRecruiter salary data. Most workers in this role earn between $50.19 and $68.70 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 Dallas, TX?

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The top searched job categories for Ai Devops Engineer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Ai Devops Engineer jobs?

Cities near Dallas, TX with the most Ai Devops Engineer job openings:

Infographic showing various Ai Devops Engineer job openings in Dallas, TX as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $124,553 per year, or $59.9 per hour.

AI DevOps Engineer-must be authorized to work in the US without any sponsorship

Atkore Management, LLC

Dallas, TX โ€ข On-site

$48.25 - $66/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago


Job description

AI DevOps Engineer

You must be authorized to work in the U.S. without any current or future sponsorship needs. This includes but is not limited to H1B, OPT, EAD, T1 and others. We will not be able to accommodate any of these conditions of employment.

Who we are:

Atkore is forging a future where our employees, customers, suppliers, shareholders, and communities are building better together – a future focused on serving the customer and powering and protecting the world.

With a global network of manufacturing and distribution facilities, Atkore is a leading provider of electrical, safety, and infrastructure solutions.

Who we are looking for:

We are looking for an AI DevOps Engineer to support Atkore’s newly established AI team. The AI DevOps Engineer will be a member of the Enterprise Architecture, Data Services and Automation (RPA/AI) team. This team works across all business and IT teams to turn Atkore strategy into executable and scalable platforms, delivering secure, resilient integration and automation to connect processes, applications and data end-to-end. This role reports to the Director of IT Enterprise Architecture, Data Services and Automation (RPA/AI) and will be based in our Mokena, Illinois or Dallas, Texas office.

What you’ll do:

The AI DevOps Engineer is responsible for designing, building, and operating the foundational infrastructure required to support Atkore’s enterprise AI capabilities. This role enables scalable, secure, and compliant AI agent development and integration across business, manufacturing, and corporate platforms.

The position partners closely with Enterprise Architecture, Information Security, Data Services, and application delivery teams to ensure AI platforms are reliable, governed, and aligned with Atkore IT standards.

  • Design, deploy, and maintain cloud and hybrid infrastructure supporting AI workloads, including container orchestration, GPU-enabled compute, and data platform integration
  • Engineer scalable, resilient environments to support AI agent execution, model serving, and experimentation across the enterprise
  • Design and manage APIs and microservices that provide secure, controlled data access for AI agents and AI-enabled applications
  • Integrate AI infrastructure with enterprise platforms such as data lakes, analytics environments, and business systems
  • Implement CI/CD pipelines, infrastructure-as-code, and automation to support AI platform reliability and repeatability
  • Establish MLOps practices for model deployment, monitoring, and lifecycle management in partnership with data and AI teams
  • Ensure AI infrastructure complies with Atkore security, privacy, and data governance standards
  • Collaborate with cybersecurity and risk teams to enforce secure identity, access management, and auditability across AI platforms
  • Partner with Enterprise Architecture to align AI platform design to long‑term technology standards and roadmaps
  • Work closely with Data Engineering, Application Integration, and other IT teams to enable AI use cases across Atkore operations

What you bring:

  • BS / BA in Computer Science, Business or related field of study
  • At least 5 years of experience in DevOps, Cloud Engineering, or Infrastructure Engineering roles
  • Expertise in containerization and orchestration technologies (e.g. Kubernetes, Docker) and infrastructure‑as‑code tools (e.g. Terraform)
  • Hands‑on experience with public cloud platforms (Azure preferred), including networking, compute, and identity services
  • Experience supporting AI/ML infrastructure platforms (e.g. Azure ML Studio, Mflow, etc)
  • Strong understanding of enterprise security principles, identity management, and secure API design
  • Familiarity with data platforms and analytics ecosystems supporting structured and unstructured enterprise data
  • Familiarity with Software Development Life Cycle and Agile delivery processes
  • Experience integrating AI platforms with ERP, MES, or manufacturing systems within an industrial or manufacturing environment desired
  • Exposure to AI governance, model risk management, or responsible AI frameworks desired
  • Strong analytical, problem-solving, and collaboration skills
  • Ability to communicate effectively with both technical and non-technical stakeholders
  • Must embrace and foster an environment that supports our core values of Accountability, Teamwork, Integrity, Respect, Excellence

      Within 3 months, you’ll:

      • Have successfully completed your onboarding and immersion program, with a full understanding of what’s expected of you as well as who the stakeholders are that you’ll work closely with
      • Have developed relationships with key stakeholders for this role
      • Have partnered with Enterprise Architecture, Cybersecurity, and Data Services to align on a baseline AI infrastructure architecture aligned to Atkore enterprise standards, security controls, and cloud strategy

       Within 6 months, you’ll:

      • Be working collaboratively with Enterprise Architecture, Cybersecurity, and Data Services to define AI infrastructure guardrails (identity, access, logging, compliance)
      • Be deploying an initial AI platform foundation (cloud and/or hybrid) capable of supporting early AI agent and model workloads
      • Be implementing core DevOps / CI‑CD patterns for AI infrastructure, enabling repeatable and secure deployments
      • Be successfully supporting first AI use cases or pilots by providing stable, secure infrastructure and rapid engineering support
      • Be working closely with peers on the IT team on achieving KPI’s, contributing ideas in the name of continuous improvement, regularly reviewing progress, establishing countermeasures where needed, and working collaboratively to achieve group objectives

      Within 12 months, you’ll:

      • Be expanding AI infrastructure to support multiple concurrent AI workloads, including model serving, data access, and agent execution
      • Be working collaboratively with the Data Services and application teams to deliver secure API and data access patterns that enable AI solutions to integrate with enterprise data and business systems
      • Be working collaboratively with Enterprise Architecture to standardize infrastructure‑as‑code and automation to reduce manual effort and improve platform resiliency
      • Be working collaboratively with Enterprise Architecture to establish MLOps and platform monitoring practices for AI reliability, cost management, and performance transparency

      Atkore is a six-time Great Place to Work© certified company and a four-time Top Workplaces USA award winner! We’re committed to creating an engaged, aligned workforce driven by a collaborative culture. Our team strives for breakthrough results and stays focused on being standout leaders. We consistently live the Atkore mission, strategic priorities, and behaviors consistent with our core values.

      Join our team and align yourself with an industry leader!

      As of the date of this posting, a good faith estimate of the current pay for this position is $107,920 - $148,390. Placement in the range depends on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, relevant experience, skills, seniority, performance, shift, travel requirements, and business or organizational needs and may change over time.  Other compensation may include, but not limited to, overtime, shift differentials, bonuses, commissions, stock, and other incentives.

      Benefits available include:

      • Medical, vision, and dental insurance
      • Life insurance
      • Short-term and long-term disability insurance
      • 401k
      • Paid Time Off
      • Paid holidays
      • Any leave required under federal, state, or local law

      Benefits are subject to vesting and eligibility requirements.

      Applications are being accepted on an ongoing basis.