Cloud / DevOps Engineer (Infrastructure & IaC)

Recruitment Room

  • 9 days ago
  • Remote
  • $156,000–$228,800

Highlights

4+ years of professional experience in cloud infrastructure, DevOps, site reliability engineering, platform engineering, or a closely related field. Support research and engineering teams by identifying knowledge gaps across cloud infrastructure, Kubernetes operations, and Infrastructure-as-Code.

Numbers & Facts

Location (
Remote
)
Salary$156,000–$228,800

Description

Cloud / DevOps Engineer (Infrastructure & IaC)

Full-Time | Remote | United States | $156,000–$228,800 annualized ($75–$110/hour)

About the Role

Join a cutting-edge GenAI team and help build the cloud infrastructure that supports the development of advanced AI models.

We’re looking for experienced Cloud and DevOps Engineers with strong, hands-on expertise in Kubernetes, AWS, Infrastructure-as-Code, and CI/CD. You’ll apply your production experience to create, evaluate, and improve technical tasks and solutions related to AI training and inference infrastructure.

This is a full-time, 40-hour-per-week opportunity for engineers who enjoy solving complex infrastructure problems and communicating technical concepts clearly.

What You’ll Do

  • Support research and engineering teams by identifying knowledge gaps across cloud infrastructure, Kubernetes operations, and Infrastructure-as-Code.

  • Design challenging, domain-specific technical tasks covering Kubernetes troubleshooting, AWS service integration, and infrastructure automation.

  • Develop accurate, well-structured solutions to complex infrastructure engineering problems.

  • Evaluate technical tasks and proposed solutions for correctness, reliability, and engineering quality.

  • Create detailed guidelines, evaluation frameworks, and rubrics for assessing Kubernetes failure diagnosis, IaC design, and CI/CD reasoning.

  • Collaborate with other infrastructure subject matter experts to maintain consistency, technical accuracy, and quality across training data.

  • Apply your production engineering experience to help improve AI systems' understanding of real-world cloud and DevOps environments.

What You Bring

  • 4+ years of professional experience in cloud infrastructure, DevOps, site reliability engineering, platform engineering, or a closely related field.

  • Strong hands-on production experience operating Kubernetes, including diagnosing and resolving cluster failures.

  • Experience troubleshooting Kubernetes environments beyond simply authoring manifests or working exclusively with managed control planes.

  • Production experience with Infrastructure-as-Code, particularly Terraform and/or AWS CDK.

  • Hands-on production experience integrating AWS services, including:

    • AWS Lambda

    • API Gateway

    • DynamoDB

  • Experience building, maintaining, and owning CI/CD pipelines.

  • Demonstrable career progression and increasing technical responsibility.

  • Strong written communication skills and the ability to explain complex technical decisions clearly.

  • Availability to work 40 hours per week during weekdays.

Compensation & Work Details

  • Compensation: $75–$110/hour

  • Annualized Compensation: $156,000–$228,800

  • Employment: Full-time W-2

  • Location: United States

  • Work Arrangement: Fully remote

  • Schedule: 40 hours per week, weekdays

  • Opportunity: Long-term potential depending on project requirements

Annualized compensation is based on 2,080 hours per year and does not represent a guaranteed annual salary.

Why Join?

  • Work at the intersection of cloud engineering, DevOps, and generative AI.

  • Apply your production infrastructure expertise to advanced AI development.

  • Tackle challenging Kubernetes, AWS, IaC, and automation problems.

  • Help shape high-quality technical training and evaluation data.

  • Collaborate with experienced engineers and technical subject matter experts.

  • Make a direct contribution to improving the capabilities of next-generation AI systems.

Equal Opportunity

All qualified applicants will be considered without regard to legally protected characteristics. Reasonable accommodations are available upon request.

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