Hybrid AI Platform Engineer - AWS SageMaker

Talentify

Coppell (TX)

Hybrid

USD 120,000 - 190,000

Full time

14 days+
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Benefits offered by this job

Health insurance
Pension plan
Paid time off
Hybrid work model
Well-being benefits

Job summary

DTCC in the United States is seeking a Systems Engineer for Platform Hosting & Engineering to design, deploy, and operate scalable AI/ML platforms on AWS. You will work on SageMaker, Bedrock, and related services to support enterprise-scale analytics and risk management platforms.

The role emphasizes automation with Terraform, CI/CD via Jenkins, and cross-account governance. You will partner with governance teams, ensure security, optimization, and reliability across distributed environments,

Qualifications

  • 4+ years of related experience
  • Bachelor's degree preferred or equivalent experience

Responsibilities

  • Design, build, and maintain AI/ML platforms on AWS
  • Manage and optimize AWS EMR clusters
  • Develop and maintain MLOps pipelines for model training and deployment
  • Implement Bedrock capabilities for secure foundation models
  • Configure SageMaker environments with network and security rules
  • Automate infrastructure provisioning using Terraform for SageMaker resources
  • Collaborate with governance and risk teams for AI/ML model approvals
  • Deploy machine learning models enabling predictive analytics

Skills

Team collaboration
Open communication
Learning mindset
Problem solving

Education

Bachelor's degree or equivalent

Tools

AWS
SageMaker
Bedrock
Terraform
Jenkins

Job description

DTCC in the United States is seeking a Systems Engineer for Platform Hosting & Engineering to design, deploy, and operate scalable AI/ML platforms on AWS. You will work on SageMaker, Bedrock, and related services to support enterprise-scale analytics and risk management platforms.

The role emphasizes automation with Terraform, CI/CD via Jenkins, and cross-account governance. You will partner with governance teams, ensure security, optimization, and reliability across distributed environments,

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