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Cloud DevOps Engineer – AI Automation — Intel
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DevOps & Cloud · Verified Opening #68

Cloud DevOps Engineer – AI Automation

business Intel location_on United States (Remote) home_work Remote Full Time

Compensation

$180K – 250K/yr

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Published Date

8 hours ago

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Work Arrangement

Remote • United States

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Open Positions

3 openings

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Experience Level

Mid-Level

overview Role Overview

About the opportunity

Join American Tech Global LLC as a Cloud DevOps Engineer focused on building secure cloud infrastructure, scalable CI/CD systems, Kubernetes environments, and AI-assisted automation for modern production workloads.

American Tech Global LLC is seeking a Cloud DevOps Engineer with hands-on experience across cloud infrastructure, container orchestration, infrastructure as code, CI/CD, observability, and AI-powered automation. In this role, you will work with engineering, security, and application teams to design and operate reliable cloud environments while automating deployment, monitoring, incident response, and infrastructure management. You will contribute to production-grade AWS environments, Kubernetes platforms, Terraform modules, GitHub Actions pipelines, and intelligent operational workflows using Python and modern AI tools. This position is well suited for professionals who have developed practical DevOps and cloud engineering capabilities through production experience, technical training, certifications, labs, or real-world projects and want to advance into cloud platform engineering, SRE, DevSecOps, and AI-enabled infrastructure roles.
task Core Responsibilities

What you will do

  • check_circle Design, build, and maintain secure cloud infrastructure using AWS services, Terraform, Linux, and infrastructure-as-code best practices.
  • check_circle Develop and optimize CI/CD pipelines using GitHub Actions or Jenkins to automate application testing, deployment, and release workflows.
  • check_circle Deploy, operate, and troubleshoot containerized applications across Docker and Kubernetes environments, including Amazon EKS.
  • check_circle Build Python and Bash automation for infrastructure provisioning, cloud operations, monitoring, configuration management, and repetitive engineering workflows.
  • check_circle Implement centralized logging, metrics, alerting, and AI-assisted observability to improve system reliability and accelerate incident investigation.
  • check_circle Partner with development and security teams to integrate DevSecOps controls, IAM policies, secrets management, vulnerability scanning, and cloud security standards into delivery pipelines.
  • check_circle Monitor infrastructure performance, availability, scalability, and cloud costs while recommending improvements to production architecture.
verified_user Candidate Profile

What we are looking for

  • arrow_circle_right 2+ years of hands-on experience in DevOps, cloud engineering, system administration, platform engineering, SRE, or a closely related technical role, including substantial real-world project experience.
  • arrow_circle_right Practical experience with AWS, Azure, or Google Cloud and a solid understanding of compute, networking, storage, IAM, load balancing, and cloud security concepts.
  • arrow_circle_right Hands-on knowledge of Docker, Kubernetes, Terraform, Git, and modern CI/CD platforms such as GitHub Actions, GitLab CI, or Jenkins.
  • arrow_circle_right Ability to automate operational tasks using Python, Bash, or a comparable scripting language.
  • arrow_circle_right Understanding of monitoring, logging, observability, infrastructure security, high availability, and production incident troubleshooting.
  • arrow_circle_right Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent professional training, certifications, and demonstrated technical experience.
code_blocks Technologies & Competencies

Skills & Tech Stack

AWS Kubernetes Docker Terraform CI/CD Python Linux AI Automation
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Why candidate applications stand out

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Verified Technical Credentials

Applications include direct proof-of-work repositories and instructor verification endorsements.

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Fast-Track Hiring Visibility

Direct internal referral channels through enterprise partners bypass automated resume discard filters.

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