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Cloud Infrastructure Engineer – AWS & ML Tooling

United States · Job Posted February 20, 2026
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Job Description

Zelis is seeking a hands-on Infrastructure Engineer to help scale and mature our cloud and automation environment. This role sits within our Data Intelligence group and works closely with the Cloud Center of Excellence (CCOE) to support production infrastructure needs for data, analytics, and ML-based applications on AWS. While this is not an MLOps engineer role, familiarity with services like SageMaker and the ability to support ML workflows from an infrastructure standpoint is important. Your core focus will be automation, deployment pipelines, cloud networking, security best practices, and ensuring the resilience and performance of our AWS-hosted environments.

Job Responsibility

  • Build and maintain AWS infrastructure using Terraform or CloudFormation (IaC)
  • Manage containerized applications using ECS and help optimize SageMaker infrastructure used by ML teams
  • Design, monitor, and improve networking architecture including VPCs, security groups, load balancers, and DNS
  • Maintain and enhance CI/CD pipelines to support automated testing, deployment, and rollback
  • Collaborate with engineering teams to optimize deployment flows and reduce friction across environments
  • Implement infrastructure security and support compliance efforts (HIPAA, SOC2, etc.)
  • Participate in cost optimization reviews and system uptime monitoring, troubleshooting as needed

Requirements

  • 5+ years of DevOps, Infrastructure, or Site Reliability Engineering experience in a cloud-native production environment
  • Deep expertise with AWS services, particularly ECS, EC2, VPC, IAM, and CloudWatch
  • Experience managing ML-adjacent infrastructure, particularly AWS SageMaker
  • Strong background in infrastructure as code (Terraform, CloudFormation)
  • Comfortable writing deployment and automation scripts in Python, Bash, or Ruby
  • Hands-on experience implementing secure, compliant cloud environments

Nice to have

  • AWS Solutions Architect Associate or Professional certification
  • Experience migrating legacy workloads to AWS
  • Familiarity with GitHub Actions, Jenkins, or other CI/CD tools
  • Understanding of supporting analytics and ML teams from an ops perspective

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