Principal DevOps Engineer - AI Cloud Platform (Remote)

General Dynamics Information Technology

United States

Remote

USD 119,000 - 161,000

Full time

14 days+
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Job summary

General Dynamics Information Technology seeks a Principal DevOps Engineer to design, build, and optimize scalable cloud infrastructure and platform services for modern application development and AI-driven solutions.

The role focuses on AWS, Amazon EKS, IaC, CI/CD automation, and data pipelines, with emphasis on AI, MLOps/AIOps, FinOps, and cloud-native best practices. You will design, deploy, and manage cloud-native infrastructure and nurture ETL workflows for analytics workloads.

Qualifications

  • 5+ years of experience in Platform Engineering, DevOps, or Cloud Engineering.
  • Hands‑on expertise with AWS, Amazon EKS, Linux, and GitLab CI/CD.
  • Strong experience with SQL, ETL automation, and building scalable data pipelines.
  • Experience implementing or supporting AI, MLOps, or AIOps platforms.
  • Strong scripting and automation skills, with a focus on cloud-native technologies.

Responsibilities

  • Design, deploy, and manage cloud-native infrastructure on AWS using GitLab CI/CD.
  • Build and support Kubernetes platforms (Amazon EKS) with a focus on scalability, security, and high availability.
  • Develop and automate ETL workflows and data pipelines for analytics and AI workloads.
  • Implement and support MLOps/AIOps and FinOps capabilities, including AI infrastructure and model deployment pipelines.
  • Troubleshoot Linux-based systems, optimize platform performance, and enforce operational best practices.

Skills

Data Pipelines
DevOps
IAAC
Kubernetes
AI/MLOps/AIOps

Tools

AWS
Amazon EKS
Linux
GitLab CI/CD
Datadog

Job description

General Dynamics Information Technology seeks a Principal DevOps Engineer to design, build, and optimize scalable cloud infrastructure and platform services for modern application development and AI-driven solutions.

The role focuses on AWS, Amazon EKS, IaC, CI/CD automation, and data pipelines, with emphasis on AI, MLOps/AIOps, FinOps, and cloud-native best practices. You will design, deploy, and manage cloud-native infrastructure and nurture ETL workflows for analytics workloads.

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