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AWS Cloud DevOps Engineer

  • Toronto, ON, Canada

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Job details

Job type
Contract
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Posting language
English
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Original job description

Iris's client, one of the Top 5 Bank in Canada is looking to hire an AWS Cloud DevOps Engineer for a long-term contract opportunity.

Our client is a Canadian multinational financial services company and the largest bank in Canada by market capitalization. The bank serves over 17 million clients and has more than 89,000 employees worldwide. Bank is serving individual consumers, small and middle market businesses and large corporations with a full range of banking, investing, asset management and other financial and risk-management products and services.

Position: AWS Cloud DevOps Engineer

Location: Toronto, ON or Berkeley Heights, NJ (Hybrid - 2-3 Day onsite/week)

Duration: Long-Term Open-Ended Contract

Key Technical Notes

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.

About Iris Software Inc.

With 4,000+ associates and offices in India, U.S.A. and Canada, Iris Software delivers technology services and solutions that help clients complete fast, far-reaching digital transformations and achieve their business goals. A strategic partner to Fortune 500 and other top companies in financial services and many other industries, Iris provides a value-driven approach - a unique blend of highly-skilled specialists, software engineering expertise, cutting-edge technology, and flexible engagement models. High customer satisfaction has translated into long-standing relationships and preferred-partner status with many of our clients, who rely on our 30+ years of technical and domain expertise to future-proof their enterprises. Associates of Iris work on mission-critical applications supported by a workplace culture that has won numerous awards in the last few years, including Certified Great Place to Work in India; Top 25 GPW in IT & IT-BPM; Ambition Box Best Place to Work, #3 in IT/ITES; and Top Workplace NJ-USA.

More about this job

Responsibilities

Design, develop, and implement AWS cloud infrastructure for AI/ML workloads, including scalable environments for model training, deployment, and lifecycle management with Amazon SageMaker. Automate infrastructure provisioning using tools such as CloudFormation and Terraform, and collaborate with data science and DevOps teams to optimize pipeline performance, cost, scalability, security, and compliance.

Requirements

The role calls for cloud development and infrastructure provisioning experience, a Cloud DevOps background, and experience with AWS CDK or Terraform. It also requires familiarity with AWS, Amazon SageMaker, infrastructure-as-code tools, and security and compliance practices for AI/ML cloud environments.

Skills

  • AWS
  • Cloud Infrastructure Provisioning
  • Cloud DevOps
  • AWS CDK
  • Terraform
  • CloudFormation
  • Amazon SageMaker
  • Infrastructure as Code
  • AI/ML Workloads
  • Model Training
  • Model Deployment
  • Lifecycle Management
  • Infrastructure Automation
  • Security and Compliance
  • Cloud Performance Optimization
  • Cost Optimization

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Engineering
  • Data & Analytics

Keywords

  • AWS
  • Cloud DevOps
  • Cloud Infrastructure
  • Infrastructure Provisioning
  • AWS CDK
  • Terraform
  • CloudFormation
  • Infrastructure as Code
  • Amazon SageMaker
  • AI/ML
  • Machine Learning
  • Model Training
  • Model Deployment
  • Lifecycle Management
  • Infrastructure Automation
  • Security
  • Compliance
  • Data Science
  • Cloud Performance Optimization
  • Cost Optimization
  • Scalability
  • AI/ML Pipelines
  • Financial Services
  • Banking

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