Agent & DevOps Platform Engineer

Toronto, ON
On-site
Posted Oct 13, 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 operate secure, reliable cloud and DevOps platform capabilities, including automation, CI/CD pipelines, container deployments, and production AI agents. Share reusable platform patterns and coach teams through working code and tools, while promoting clear ownership, operational simplicity, and a strong developer experience.

Job details

K&K Global Talent Solutions Inc is an international recruiting agency that has been providing technical resources in Canada region since 1993. This position is with one of our clients in Canada, who is actively hiring candidates to expand their teams. Role: Agent & DevOps Platform Engineer Employment type: Fulltime Technology: Java, .NET, Groovy, or Node.js, AI/LLM Location: onsite (Toronto, ON) Job Description- • 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 Note: Applicants for employment in Canada should possess work authorization which does not require sponsorship by the employer for a visa

What you’ll do

Requirements

Requires 3–5+ years of enterprise CI/CD, cloud, and platform engineering experience, strong Python skills, hands-on AWS and IAM experience, and production container experience. Candidates should also have experience integrating AI/LLM tools or agents and understand LLMOps, Infrastructure as Code, Git-based release workflows, and security-focused DevOps practices.