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Agent & DevOps Platform Engineer-6

Realign
Toronto, CAN
Full-time
Onsite
Discovered 3 weeks ago
CI/CDCloud and platform engineeringPythonJava, .NET, Groovy, or Node.jsAWSAWS IAM

Full Job Posting

Role overview

Agent & DevOps Platform Engineer role based in Toronto, with full-time employment and an onsite work model.

The role focuses on enterprise platform engineering, cloud automation, AI agents, and DevSecOps.

Required skillsets

  • 3–5+ years of hands-on CI/CD, cloud, and platform engineering experience in enterprise environments.
  • Strong Python for automation, API integrations, infrastructure tooling, agent services, and production scripting.
  • Working experience with at least one additional ecosystem such as Java, .NET, Groovy, or Node.js.
  • Hands-on AWS production workload design or operations experience.
  • AWS IAM knowledge covering roles, policies, trust relationships, cross-account access, least privilege, and service authentication.
  • Production container experience with Docker and Kubernetes, Amazon ECS, or Amazon EKS.
  • Production or near-production experience building or integrating AI/LLM-based tools or agents.
  • LLMOps knowledge covering prompts, tools, agent architectures, evaluation, observability, and reliability.
  • Git workflows, build automation, release pipelines, Infrastructure as Code, configuration management, and cloud-native deployments.
  • DevSecOps mindset that treats security as a design constraint.

Good-to-have skills

  • AWS services such as EKS, ECS, ECR, Lambda, Bedrock, CloudWatch, S3, Secrets Manager, Systems Manager, and VPC.
  • Terraform, CloudFormation, or AWS CDK; multi-account AWS and enterprise identity patterns.
  • Kubernetes operations, Helm, service accounts, ingress, networking, and workload security.
  • AI integration into developer platforms or enterprise tooling; LangChain, LlamaIndex, or custom agent toolchains.
  • Enabling DevOps practices across teams or business units; Scrum, Kanban, or SAFe delivery experience.

Role approach

  • Build and share working code, pipelines, agents, and reusable platform patterns.
  • Think through downstream effects of cloud, identity, container, and automation decisions.
  • Define the right problem in ambiguous situations and support technical decisions with evidence.
  • Learn quickly, experiment deliberately, and ship when solutions are ready.
  • Make secure defaults, clear ownership, and developer experience integral to platform adoption.

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