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AI Platform Engineer – DevOps & LLMOps

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
Posted

Original job description

Position: AI Platform Engineer – DevOps & LLMOps

Location: Toronto, ON (Onsite)

Experience Required:- 5 - 8 years

Key Requirements

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.
More about this job

Responsibilities

Build and share reusable platform patterns, pipelines, and AI agents while coaching teams through working implementations. Make evidence-based decisions about cloud, identity, containers, automation, security, reliability, and developer experience, and turn ambiguous problems into secure, maintainable solutions.

Requirements

Requires 5–8 years of experience, including hands-on enterprise CI/CD, cloud, and platform engineering, strong Python skills, production AWS experience, and container deployment experience. Candidates should also have practical AWS IAM and Infrastructure as Code knowledge, production or near-production AI/LLM integration experience, and a strong DevSecOps mindset.

Skills

  • Python
  • CI/CD
  • AWS
  • AWS IAM
  • Docker
  • Kubernetes
  • Amazon ECS
  • Amazon EKS
  • LLMOps
  • AI Agents
  • Infrastructure as Code
  • DevSecOps
  • Terraform
  • CloudFormation
  • Helm
  • Git-Based Workflows

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Engineering
  • Security & Safety
  • Management & Leadership

Keywords

  • AI Platform Engineering
  • DevOps
  • LLMOps
  • Python
  • Java
  • .NET
  • Groovy
  • Node.js
  • CI/CD
  • AWS
  • AWS IAM
  • Docker
  • Kubernetes
  • Amazon ECS
  • Amazon EKS
  • Amazon ECR
  • AWS Lambda
  • Amazon Bedrock
  • Amazon CloudWatch
  • Amazon S3
  • AWS Secrets Manager
  • AWS Systems Manager
  • Amazon VPC
  • Terraform
  • CloudFormation
  • AWS CDK
  • Helm
  • LangChain
  • LlamaIndex
  • Infrastructure as Code

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