AWS Cloud DevOps Engineer

FutureTech Consultants LLC

Berkeley Heights (NJ)

Hybrid

USD 120,000 - 160,000

Full time

7 days ago
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Job summary

FutureTech Consultants LLC in Berkeley Heights, NJ, is seeking an AWS Cloud DevOps Engineer for a long-term contract. The position is hybrid, requiring three days onsite weekly, and focuses on building secure, scalable AWS infrastructure for AI/ML workloads.

You will design and implement infrastructure using CDK/Terraform, CloudFormation, and SageMaker for training, deployment, and lifecycle management, while collaborating with data science and DevOps teams to optimize performance and cost.

Qualifications

  • AWS cloud development and IaC experience with CDK/Terraform.
  • Design, develop, and implement cloud infrastructure for AWS focusing on AI/ML workloads.
  • Build scalable environments with SageMaker for model training, deployment, and lifecycle management.
  • Automate provisioning with CloudFormation or Terraform while meeting security/compliance standards.
  • Collaborate with data science and DevOps teams to optimize performance and cost of AI/ML pipelines.

Skills

Cloud DevOps
IaC Automation
AWS Cloud
AI/ML Workloads

Tools

AWS CDK
Terraform
CloudFormation
Amazon SageMaker

Job description

Role: AWS Cloud DevOps Engineer

Location: Berkeley Heights, NJ (Hybrid, 3 days onsite in a week)

Duration: Long Term Contract

Mode of Interview: Video Round followed by In-person

Must Have:
  • AWS cloud developer for infrastructure provisioning skills and Cloud DevOps background and worked/working experience on CDK/TerraForm.
  • Design, develop, and implement cloud infrastructure solutions on AWS with a focus on AI/ML workloads.
  • Build and manage scalable environments using Amazon SageMaker for model training, deployment, and lifecycle management.
  • Automate infrastructure provisioning using IaC tools (e.g., CloudFormation, Terraform) adhering to security and compliance standards.
  • Collaborate with data science and DevOps teams to optimize performance, cost, and scalability of AI/ML pipelines in the cloud.
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