AWS DevOps Engineer, MLOps

Capstone Integrated Solutions

. Design and maintain CI/CD pipelines supporting automated testing, deployment, and change management across CDP, data lake, marketing cloud, and migration workstreams .

Posted 9/15/2026full-timeRemote • New York • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining CI/CD pipelines, managing AWS environments, and implementing infrastructure as code using AWS CDK or Terraform. Proficient in MLOps practices on Amazon SageMaker and experienced in data pipeline infrastructure management across AWS services.

Highest-signal resume keywords

CI/CD Pipeline DesignAWS Environment ManagementInfrastructure As CodeMLOps PracticesAWS Security Best Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AWS CDKTerraformAmazon SageMakerAWS GlueAWS LambdaAWS Step FunctionsAWS IAMAWS Lake FormationAWS CodePipelineGitHub Actions

Soft Skills

CollaborationChange ManagementDocumentation

Tools & Technologies

CloudWatchCloudTrailAWS ConfigAWS DataSyncAmazon Bedrock

Certifications & Qualifications

AWS DevOps Engineer ProfessionalAWS Solutions ArchitectAWS Machine Learning Specialty

Industry Keywords

MLOpsData ComplianceAgileScrumEnterprise SaaS

Tech Stack

Tools & technologies

AWSAzureCloudJenkinsTerraform

About the role

Key responsibilities & impact

Design and maintain CI/CD pipelines supporting automated testing, deployment, and change management across CDP, data lake, marketing cloud, and migration workstreams
Provision and manage AWS environments including S3 buckets, Glue jobs, networking, IAM, and VPCs for non-production development and staging
Ensure environments are logically segregated with no public internet access per SOW requirements
Implement and enforce infrastructure as code using AWS CDK or Terraform
Manage the MLOps lifecycle on Amazon SageMaker, including model versioning, deployment automation, endpoint monitoring, and automated retraining triggers
Support Amazon Bedrock integration deployments by managing prompt versioning, model configuration, and API endpoint reliability
Implement and maintain data lake security infrastructure using AWS Lake Formation, including row-level security, column-level encryption, and IAM permission boundaries
Support Azure-to-AWS migration execution, including target environment provisioning, AWS DataSync jobs, cutover procedures, freeze periods, and rollback plans
Monitor pipeline health, data job execution, and ML endpoint performance across AWS Glue, Step Functions, Lambda, Kinesis, and SageMaker using CloudWatch and AWS-native observability tools
Implement AWS cost optimization practices and provide guidance on Azure resource decommissioning post-migration
Coordinate change management processes, including documenting changes, obtaining approvals, executing peer-reviewed deployments, and maintaining rollback procedures
Collaborate with Data/ML and Full Stack engineers across data pipelines, ML inference, and application layers
Contribute to operations runbooks, deployment guides, and infrastructure documentation

Requirements

What you’ll need

4+ years of DevOps or cloud infrastructure experience, with at least 2+ years on AWS
Hands-on experience with CI/CD tooling such as GitHub Actions, AWS CodePipeline, Jenkins, or equivalent in a multi-environment AWS setup
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
Experience with AWS IAM, Lake Formation, VPC, and security best practices for data environments
Familiarity with AWS monitoring and observability tools including CloudWatch, CloudTrail, and AWS Config
Experience supporting data pipeline infrastructure including AWS Glue, Step Functions, Lambda, Kinesis, and S3
Strong understanding of environment management, change control processes, and rollback procedures in enterprise delivery contexts
Ability to work in Agile/Scrum teams alongside AWS Professional Services with structured change approval workflows
Azure infrastructure and Azure-to-AWS migration experience (nice to have)
Familiarity with Amazon Bedrock deployment and API management (nice to have)
Experience with Amazon Connect or omnichannel platform infrastructure (nice to have)
Knowledge of data compliance and privacy controls (nice to have)
AWS Certification such as DevOps Engineer Professional, Solutions Architect, or Machine Learning Specialty (nice to have)
Exposure to Kiro CLI or AI-assisted infrastructure tooling (nice to have)
Background in real estate, property management, or enterprise SaaS environments (nice to have)

Benefits

Comp & perks

Full-time contract employment
Equal opportunity employer committed to diversity and an inclusive, safe environment
Learning and professional growth culture
Knowledge sharing and continuous learning culture