DevOps/AWS Platform Engineer

We are looking for a DevOps/AWS Platform Engineer to join a long-term contract engagement based in West Des Moines, Iowa. This hands-on platform engineering role focuses on modernizing cloud deployment patterns, strengthening infrastructure decisions, and accelerating delivery through AI-assisted development tools while maintaining high engineering standards. The person in this role will partner closely with DevOps peers to review automated changes critically, validate outcomes through established testing methods, and build reliable, reusable deployment capabilities across the AWS ecosystem.Responsibilities:• Redesign container build and publication processes so application images can be delivered through Amazon ECR and GitHub package repositories in alignment with target platform needs.• Rework deployment automation to support containerized workloads on AWS Fargate, including service definitions, networking, permissions, logging, load balancing, and release verification using existing GitHub Actions workflows.• Replace Azure-based identity and access patterns with AWS-native role design and federated access models integrated with organizational authentication groups.• Transition secrets and configuration management to AWS services such as Secrets Manager and Parameter Store to support secure runtime access.• Convert Terraform configurations from Azure-focused implementations to AWS-based infrastructure modules, including updates to providers, reusable components, and remote state management.• Update GitHub Actions pipelines, runners, and reusable workflows to align with the target GitHub organization and AWS account trust relationships.• Create and refine deployment pipelines that enable reusable delivery into AWS Fargate environments for the applications and tools supported by this platform.• Adapt scripts, instructions, and developer tooling so they operate consistently inside Ubuntu-based Coder workspaces, including environment setup, credentials handling, and workflow expectations.• Use AI-assisted coding tools to speed implementation, while independently inspecting, testing, and validating every change before release.• Produce validation evidence for migrated capabilities using the existing evaluation framework and prepare concise handoff documentation for internal engineering teams.