Remote Principal AI/ML DevOps Engineer

General Dynamics Information Technology, Inc.; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

General Dynamics Information Technology, Inc. is seeking a Principal DevOps Engineer to design, build, and optimize scalable cloud infrastructure and platform services.

The role emphasizes AWS, EKS, IaC, CI/CD automation, and AI-driven solutions for modern application development. Responsibilities include deploying cloud-native infrastructure, managing EKS clusters, automating ETL workflows, and enabling MLOps/AIOps and FinOps capabilities to support analytics and AI 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

AWS

Kubernetes

GitLab CI/CD

ETL automation

SQL

Python

Automation scripting

AI/MLOps/AIOps

FinOps

Linux

Datadog

Tools

Amazon EKS

Datadog

Linux

GitLab CI/CD

Job description

General Dynamics Information Technology, Inc. is seeking a Principal DevOps Engineer to design, build, and optimize scalable cloud infrastructure and platform services.

The role emphasizes AWS, EKS, IaC, CI/CD automation, and AI-driven solutions for modern application development. Responsibilities include deploying cloud-native infrastructure, managing EKS clusters, automating ETL workflows, and enabling MLOps/AIOps and FinOps capabilities to support analytics and AI workloads.