AWS DevOps Engineer / MLOps

Role overview A hands-on AWS DevOps engineering position focused on building automated cloud, data, and AI-enabled infrastructure for enterprise environments. The role blends traditional DevOps responsibilities with MLOps lifecycle management on Amazon SageMaker, supporting data pipelines, machine learning endpoints, and ongoing Azure-to-AWS migration work alongside professional services teams.

Responsibilities - Design and maintain CI/CD pipelines for automated testing, deployment, and change management across data lake, marketing cloud, migration, and other workstreams. - Provision and manage AWS environments including S3, Glue, networking, IAM, and VPCs for development and staging, keeping environments logically segregated and internet-isolated. - Implement infrastructure as code with AWS CDK or Terraform to ensure reproducible, auditable configurations across workstreams. - Manage the MLOps lifecycle on Amazon SageMaker, covering model versioning, deployment automation, endpoint monitoring, and automated retraining triggers for use cases such as lead scoring and predictive maintenance. - Support Amazon Bedrock integration deployments, including prompt versioning, model configuration, and API endpoint reliability. - Coordinate change management processes: documenting changes, securing approvals, executing peer-reviewed deployments, and maintaining rollback procedures. - Monitor pipeline health and ML endpoint performance using CloudWatch and other AWS-native observability tools, and apply cost optimization practices across services.

Requirements - 4+ years of DevOps or cloud infrastructure experience, with at least 2+ years hands-on on AWS. - Practical experience with CI/CD tooling such as GitHub Actions, AWS CodePipeline, or Jenkins in multi-environment AWS setups. - Proficiency with infrastructure as code using AWS CDK, CloudFormation, or Terraform. - Working knowledge of MLOps practices on Amazon SageMaker, including model deployment, endpoint management, monitoring, and pipeline automation. - Solid grasp of AWS IAM, Lake Formation, VPC, and security best practices for data environments, plus familiarity with CloudWatch, CloudTrail, and AWS Config. - Understanding of environment management, change control, and rollback procedures in enterprise delivery contexts, with the ability to operate in Agile/Scrum alongside structured change approval workflows.

Nice to have - Experience with Azure infrastructure and Azure-to-AWS migration work using DataSync, networking changes, and decommissioning. - Familiarity with Amazon Bedrock deployment and API management, Amazon Connect, or omnichannel platform infrastructure. - Knowledge of data compliance and privacy controls such as encryption at rest and in transit.

Benefits and work setup - Full-time contract role.