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Cloud Platform Engineer – AWS, Python, DevOps & AI/LLM

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Summary

Cloud platform engineer in Toronto designing and operating AWS infrastructure and CI/CD pipelines with heavy Python automation, containers (Docker/Kubernetes/ECS/EKS), IAM security, and building production AI/LLM tools and agents using LLMOps practices.

Required Skillsets:

  • 3–5+ years of hands‑on CI/CD, cloud, and platform engineering experience in enterprise environments.

Cloud Platform Engineer – AWS, Python, DevOps & AI/LLM

Required Skillsets:

  • 3–5+ years of hands‑on CI/CD, cloud, and platform engineering experience in enterprise environments.
  • Strong proficiency in Python for automation, API integrations, infrastructure tooling, agent services, and production scripting.
  • Working experience with at least one additional language or ecosystem such as Java, .NET, Groovy, or Node.js.
  • Hands‑on AWS experience designing or operating production workloads.
  • Practical knowledge of AWS IAM, including roles, policies, trust relationships, cross‑account access, least privilege, and service‑to‑service authentication.
  • Production experience building and deploying containers with Docker and a container platform such as Kubernetes, Amazon ECS, or Amazon EKS.
  • Experience building or integrating AI/LLM‑based tools or agents in production or near‑production environments.
  • Strong understanding of LLMOps concepts: prompt management, tool use, agent architectures, evaluation, observability, and reliability.
  • Experience with Git‑based workflows, build automation, and release pipelines at scale.
  • Hands‑on experience with Infrastructure as Code, configuration management, and cloud‑native deployments.
  • DevSecOps mindset — security is a design constraint, not a checklist item.

Good to Have Skills:

  • Experience with AWS services such as EKS, ECS, ECR, Lambda, Bedrock, CloudWatch, S3, Secrets Manager, Systems Manager, and VPC.
  • Experience with Terraform, CloudFormation, or AWS CDK.
  • Experience designing multi‑account AWS environments and implementing enterprise identity and access patterns.
  • Familiarity with Kubernetes operations, Helm, service accounts, ingress, networking, and workload security.
  • Experience integrating AI into developer platforms or enterprise tooling, rather than only building standalone applications.
  • Prior work on agentic orchestration frameworks such as LangChain, LlamaIndex, or custom toolchains.
  • Experience enabling DevOps practices across multiple teams or business units.
  • Agile delivery experience using Scrum, Kanban, or SAFe.

Roles and Responsibilities:

  • You build things and share them — your coaching is your working code, your pipelines, your agents, and your reusable platform patterns.
  • You think in systems: you understand the downstream effects of cloud, identity, container, and automation decisions.
  • You're comfortable in ambiguity and can define the right problem before solving the wrong one.
  • You have strong opinions on automation, reliability, security, IAM, and operational simplicity — and can defend them with evidence.
  • You learn fast, experiment deliberately, and know when to stop experimenting and ship.
  • You understand that secure defaults, clear ownership, and good developer experience are essential to platform adoption.

Skills

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