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PeoplePilot Linkedin · Posted 19d ago

Agent & DevOps Platform Engineer

Canada

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Indexed 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.



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