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Junior DevOps and Cloud Engineer – AI Infrastructure — Amazon Web Services (AWS)
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DevOps & Cloud · Verified Opening #83

Junior DevOps and Cloud Engineer – AI Infrastructure

business Amazon Web Services (AWS) location_on Dallas, TX (Hybrid) or Remote, USA apartment Hybrid Full Time

Compensation

$75K – 100K/yr

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Published Date

5 days ago

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Work Arrangement

Hybrid • Dallas, TX or Remote, USA

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Open Positions

2 openings

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Experience Level

Entry-Level to Mid-Level

overview Role Overview

About the opportunity

Launch your career in cloud infrastructure, DevOps automation, and AI-powered operations. Join a collaborative engineering team to build reliable deployment pipelines, manage cloud environments, and implement intelligent monitoring solutions while developing industry-ready technical skills.

The Junior DevOps and Cloud Engineer role focuses on building, automating, and maintaining scalable cloud infrastructure and modern software delivery workflows. You will collaborate with experienced engineers to support cloud deployments, improve system reliability, streamline CI/CD pipelines, and explore AI-assisted approaches to infrastructure monitoring and operational automation. This opportunity is suited to candidates with foundational DevOps and cloud knowledge who are ready to apply their skills to practical engineering challenges. The ideal candidate is curious, analytical, comfortable learning new technologies, and passionate about automation, cloud computing, and artificial intelligence. You will gain exposure to modern cloud platforms, containerized applications, infrastructure as code, and production monitoring practices, with opportunities to grow into specialized roles in cloud engineering, platform engineering, SRE, or AI infrastructure.
task Core Responsibilities

What you will do

  • check_circle Assist in building and maintaining CI/CD pipelines using GitHub Actions, Jenkins, or AWS CodePipeline to automate application builds, testing, and deployments.
  • check_circle Support cloud infrastructure provisioning and configuration using AWS services, Terraform, and infrastructure-as-code best practices.
  • check_circle Deploy and manage containerized applications using Docker and Kubernetes, including AWS Elastic Kubernetes Service (EKS) where applicable.
  • check_circle Monitor application performance, cloud resources, and system availability using tools such as Amazon CloudWatch, Prometheus, and Grafana.
  • check_circle Develop Python or Bash scripts to automate repetitive operational tasks, deployment workflows, and infrastructure maintenance.
  • check_circle Explore AI-assisted monitoring, log analysis, anomaly detection, and operational troubleshooting to improve system reliability and efficiency.
  • check_circle Collaborate with development, security, and operations teams to troubleshoot incidents, document solutions, and apply cloud security and cost-optimization practices.
verified_user Candidate Profile

What we are looking for

  • arrow_circle_right Foundational knowledge of DevOps principles, software development lifecycles, and CI/CD pipelines, demonstrated through coursework, projects, internships, or professional experience.
  • arrow_circle_right Working knowledge of Linux, Git, Docker, and basic networking concepts, including DNS, HTTP/HTTPS, and TCP/IP.
  • arrow_circle_right Basic understanding of at least one cloud platform, preferably AWS, with familiarity with services such as EC2, S3, IAM, and CloudWatch.
  • arrow_circle_right Exposure to Kubernetes, Terraform, Jenkins, GitHub Actions, or comparable automation and infrastructure management tools.
  • arrow_circle_right Basic scripting ability in Python or Bash, along with a willingness to learn AI-assisted automation, monitoring, and troubleshooting techniques.
  • arrow_circle_right Strong problem-solving, communication, documentation, and teamwork skills; a relevant degree, certification, bootcamp, or practical project portfolio is beneficial.
code_blocks Technologies & Competencies

Skills & Tech Stack

DevOps AWS Cloud Docker Kubernetes CI/CD Terraform Python 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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