Cloud Engineer 3 - AWS, Kubernetes & NVIDIA AI Infrastructure (120051-1)

Cullerton Group
  • Chicago, IL
  • $92
  • Instant Apply
1 day ago

Job Description

Cullerton Group has a new opportunity for a Cloud Engineer 3 – AWS, Kubernetes & NVIDIA AI Infrastructure in Chicago, IL; Dallas, TX; Peoria, IL; or Broomfield, CO. The work will be performed on a hybrid schedule requiring 2 days onsite per week, with additional office attendance as requested. This is a long-term contract opportunity that can lead to permanent employment with our client. Compensation is $92/hr W-2 plus full benefits (vision, dental, health insurance, 401k, and holiday pay).
Job Summary
The Cloud Engineer 3 will support enterprise cloud infrastructure and platform engineering initiatives, enabling software development teams to build, test, and deploy applications in AWS environments. This role focuses on managing Amazon EKS, Kubernetes, Docker, and NVIDIA AI workload orchestration platforms, including NVIDIA Run and NVIDIA OSMO. The engineer will develop and maintain cloud infrastructure using Infrastructure as Code, automate deployments through GitHub Actions CI/CD pipelines, and troubleshoot complex cloud infrastructure and application issues. The ideal candidate will have extensive hands-on AWS experience, strong container orchestration and automation skills, and the ability to independently support multiple engineering teams in a collaborative environment.
Key Responsibilities
  • Design, develop, provision, and maintain AWS cloud infrastructure using Infrastructure as Code technologies such as AWS CloudFormation, Terraform, or AWS CDK.
  • Administer, configure, troubleshoot, and optimize Amazon EKS, Kubernetes, and Docker environments, ensuring scalable and reliable infrastructure for enterprise applications.
  • Support NVIDIA Run, NVIDIA OSMO, or comparable workload orchestration platforms used to manage AI and GPU-based computing workloads.
  • Develop and maintain GitHub Actions CI/CD pipelines, GitHub repositories, and YAML-based automation workflows to support application builds, testing, infrastructure deployments, and software releases.
  • Collaborate with software development and platform engineering teams to troubleshoot complex infrastructure and application issues, support integration and acceptance testing, improve operational reliability, and maintain engineering best practices.
Required Qualifications
  • High school diploma or equivalent required; a college degree is not required.
  • 5–7 years of relevant software development or cloud engineering experience, including at least 5 years of hands-on AWS cloud experience.
  • Minimum 5 years of professional experience in a Cloud Engineer or closely related cloud infrastructure engineering role.
  • Strong experience using GitHub and GitHub Actions for source control, YAML-based CI/CD workflows, and deployment automation.
  • Hands-on experience writing, deploying, and maintaining AWS cloud infrastructure using AWS CloudFormation, Terraform, or AWS CDK.
  • Proficiency with Amazon EKS, Kubernetes, and Docker, including container orchestration, deployment, troubleshooting, and infrastructure management.
  • Experience with NVIDIA Run, NVIDIA OSMO, or comparable workload orchestration systems.
  • Strong knowledge of cloud infrastructure operations, software development workflows, and application deployment processes.
  • Demonstrated ability to troubleshoot complex cloud infrastructure, application, and technical issues independently.
  • Strong analytical thinking, problem-solving, and technical communication skills.
  • Experience collaborating with cross-functional software engineering, cloud infrastructure, and application development teams.
  • Ability to work independently on complex engineering assignments while maintaining high software quality standards.
  • Willingness to provide occasional off-shift or weekend technical support when required.
  • Ability to work on a hybrid schedule with 2 days onsite per week, plus additional days as requested, in one of the designated office locations.
Preferred Qualifications
  • AWS Associate or Professional-level certification, such as AWS Certified Solutions Architect, AWS Certified Developer, or AWS Certified DevOps Engineer.
  • NVIDIA-related technical certifications.
  • Hands-on experience with NVIDIA GPUs and GPU-accelerated infrastructure supporting AI or machine learning workloads.
  • Experience managing enterprise-scale Kubernetes environments and optimizing containerized infrastructure.
  • Experience supporting AI development platforms, GPU resource allocation, and distributed workload orchestration.
  • Advanced experience with Infrastructure as Code, automated infrastructure provisioning, and reusable cloud deployment patterns.
  • Strong background in troubleshooting AWS infrastructure, Kubernetes workloads, and complex deployment issues.
  • Experience supporting multiple engineering teams as part of a centralized cloud platform or shared infrastructure services organization.
  • Experience improving platform scalability, reliability, development efficiency, and cloud engineering practices.
  • Previous experience supporting large enterprise, manufacturing, industrial technology, or global engineering organizations.
Why This Role?
This position offers an opportunity to work with advanced AWS cloud technologies, Kubernetes infrastructure, and NVIDIA AI workload orchestration platforms supporting a global leader in heavy machinery and manufacturing. You will contribute to cloud environments that enable engineering teams to develop, test, and deploy innovative software and AI solutions while expanding your expertise in infrastructure automation, container orchestration, and GPU-based computing. Cullerton Group provides a professional environment with growth potential, comprehensive benefits, and opportunities to develop specialized skills in cloud platform engineering and emerging AI infrastructure technologies.

 

Numbers & Facts

LocationChicago, IL
Salary$92

Skills

  • Acceptance Testingunmatched
  • Amazon Web Services (AWS)unmatched
  • Analysis Skillsunmatched
  • Artificial Intelligence (AI)unmatched
  • Automationunmatched
  • Best Practicesunmatched
  • Cloud Applicationsunmatched
  • Cloud Computingunmatched
  • Communication Skillsunmatched
  • Continuous Deployment/Deliveryunmatched
  • Continuous Integrationunmatched
  • Cross-Functionalunmatched
  • DevOpsunmatched
  • Dockerunmatched
  • Emerging Technologyunmatched
  • Engineeringunmatched
  • Enterprise Applicationsunmatched
  • GPU (Graphics Processing Unit)unmatched
  • GitHubunmatched
  • Heavy Equipment/Vehiclesunmatched
  • Identify Issuesunmatched
  • Infrastructure Softwareunmatched
  • Integration Testingunmatched
  • Machine Learningunmatched
  • Manufacturingunmatched
  • Operational Improvementunmatched
  • Problem Solving Skillsunmatched
  • Quality Managementunmatched
  • Quality Metricsunmatched
  • Reliability Engineeringunmatched
  • Resource Managementunmatched
  • Software Administrationunmatched
  • Software Developmentunmatched
  • Software Engineeringunmatched
  • Software Testingunmatched
  • Source Code/Configuration Management (SCM)unmatched
  • Team Playerunmatched
  • Technical Supportunmatched
  • Test Plan/Scheduleunmatched
  • Testingunmatched

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