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Agent & DevOps Platform Engineer

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Experience
3–5+ years of experience in DevOps, cloud, CI/CD, or platform engineering.
Posting language
English
Posted

Original job description

We are looking for an Agent & DevOps Platform Engineer to join our team in Toronto, ON (Onsite). The ideal candidate will have strong hands-on experience in AWS, Python, CI/CD, Kubernetes, Docker, Infrastructure as Code, and DevSecOps, along with practical experience building or integrating AI/LLM-based tools and agents. The role involves developing secure, scalable, and reusable cloud-native platforms, automation, pipelines, and AI-powered developer solutions in an enterprise environment.

Key Requirements

  • 3–5+ years of experience in DevOps, cloud, CI/CD, or platform engineering.
  • Strong Python programming skills for automation, APIs, infrastructure tooling, and scripting.
  • Experience with AWS production environments.
  • Strong knowledge of AWS IAM, including roles, policies, trust relationships, cross-account access, and least privilege.
  • Hands-on experience with Docker and Kubernetes, EKS, or ECS.
  • Strong experience with CI/CD, Git workflows, build automation, and release pipelines.
  • Experience with Infrastructure as Code, such as Terraform, CloudFormation, or AWS CDK.
  • Experience building or integrating AI/LLM tools, agents, or developer platforms.
  • Understanding of LLMOps, including prompt management, tool use, agent architecture, evaluation, observability, and reliability.
  • Experience with cloud-native deployments and DevSecOps practices.
  • Working knowledge of an additional language/ecosystem such as Java, .NET, Groovy, or Node.js.
  • Strong problem-solving, communication, and collaboration skills.

Key Responsibilities

  • Design, build, and maintain AWS-based developer and DevOps platforms.
  • Develop automation, infrastructure tooling, APIs, and production scripts using Python.
  • Build and manage scalable CI/CD pipelines and release automation.
  • Deploy and operate containerized applications using Docker and Kubernetes/EKS/ECS.
  • Implement secure AWS IAM, authentication, and access-control patterns.
  • Develop and integrate AI/LLM-based agents and tools into enterprise developer platforms.
  • Apply LLMOps practices for agent evaluation, observability, reliability, and tool management.
  • Implement Infrastructure as Code and reusable cloud deployment patterns.
  • Promote DevSecOps, security-by-design, secure defaults, and operational simplicity.
  • Create reusable platform patterns and solutions that can be adopted across multiple teams.
  • Troubleshoot complex cloud, automation, identity, and platform issues.
  • Coach and support engineering teams through reusable code, pipelines, automation, and platform solutions.
  • Work effectively in ambiguous environments and turn experimental solutions into reliable production capabilities.
More about this job

Responsibilities

Design and maintain AWS-based developer platforms and scalable CI/CD pipelines. Develop and integrate AI/LLM-based agents and tools into enterprise developer environments using Python.

Requirements

Requires 3-5+ years of experience in DevOps or platform engineering with strong Python and AWS production environment skills. Must have practical experience with containerization, Infrastructure as Code, and building AI/LLM-based tools.

Skills

  • AWS
  • Python
  • CI/CD
  • Kubernetes
  • Docker
  • Infrastructure as Code
  • DevSecOps
  • AI/LLM Tools
  • LLMOps
  • Terraform
  • AWS IAM
  • EKS
  • ECS
  • Git
  • Cloud-native Platforms
  • API Development

Visa sponsorship

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Categories

  • Software
  • Technology
  • Engineering
  • Data & Analytics

Keywords

  • AWS
  • Python
  • CI/CD
  • Kubernetes
  • Docker
  • Infrastructure as Code
  • DevSecOps
  • AI
  • LLM
  • LLMOps
  • Terraform
  • CloudFormation
  • AWS CDK
  • AWS IAM
  • EKS
  • ECS
  • Git
  • Java
  • .NET
  • Groovy
  • Node.js
  • Cloud-native
  • Automation
  • API
  • Agent Architecture
  • Observability
  • Reliability
  • Data Infrastructure
  • Analytics
  • Enterprise Environment

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