Cloud Infrastructure Engineer – AWS & ML Tooling

Position Overview

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.

What You’ll Do

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

Required Qualifications

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

Preferred

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

What This Role Is Not

Not a data science or MLOps role (though you'll support ML infrastructure)

Not a high-level strategic platform architect

Not focused on theoretical platform ownership or innovation fluff
This is a practical, engineering-first role focused on well-structured, scalable infrastructure and automation in AWS.

Location and Workplace Flexibility

We have offices in Atlanta GA, Boston MA, Morristown NJ, Plano TX, St. Louis MO, St. Petersburg FL, and Hyderabad, India.

We foster a hybrid and remote friendly culture, and all our employee's work locations are based on the needs of the position and determined by the Leadership team.

In-office work and activities, if applicable, vary based on the work and team objectives in accordance with Company policies.