Agent & DevOps Platform Engineer

Toronto, ON
On-site
Posted Oct 17, 2026
1 position

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Employment type: Full-time
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Build and automate scalable cloud platforms, secure infrastructure, and AI-powered engineering solutions, with a focus on reliability and operational excellence. Develop reusable platform patterns, pipelines, and agents while guiding teams and making evidence-based decisions about automation, security, identity, and operations.

Job details

Position: Agent & DevOps Platform Engineer Location: Toronto, ON (Onsite) Employment Type: Full Time Experience Required: 7 + Years Role Summary: We are looking for an experienced Agent & DevOps Platform Engineer with 5 + years of expertise in AWS, Python, Kubernetes, CI/CD, DevSecOps, and AI/LLM platforms. In this role, you'll build and automate scalable cloud platforms, implement secure infrastructure, and drive AI-powered engineering solutions while ensuring reliability, security, and operational excellence. Required Skills: 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 Key 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 Good to have Skills: Experience with AWS services such as EKS, ECS, ECR, Lambda, Bedrock, Cloud Watch, S3, Secrets Manager, Systems Manager, and VPC Experience with Terraform, Cloud Formation, 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 Lang Chain, Llama Index, or custom toolchains Experience enabling DevOps practices across multiple teams or business units Agile delivery experience using Scrum, Kanban, or SAFe

What you’ll do

Requirements

Requires substantial enterprise platform engineering experience, strong Python skills, hands-on AWS and IAM expertise, and production experience with containers, CI/CD, and Infrastructure as Code. Candidates should also understand LLMOps and production AI agents, have experience with another programming language or ecosystem, and apply security as a core design constraint.