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Note to applicants: Please submit both a cover letter and resume in the "Resume/CV and Support Materials" field. Do not submit your application until both documents are attached.

Amyantek

DevOps Engineer / Senior Cloud Platform Engineer

Toronto, ON, Canada

Job type: Contract
Apply by: Oct 26, 2026
Posting language: English
Posted: Sep 26, 2026

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Original job description

Senior DevOps Engineer / Senior Cloud Platform Engineer

Location: Downtown Toronto, ON

Work Model: Hybrid – 2 days onsite per week, 3 days remote

Contract: 6 months, with possibility of extension

Start Date: ASAP

End Client: Confidential

About the Role

We are seeking a highly hands-on Senior DevOps Engineer / Senior Cloud Platform Engineer to own and evolve a production AWS cloud platform.

This role requires deep AWS and Kubernetes expertise, with Amazon EKS being a critical requirement. We are specifically looking for someone who has personally designed, built, operated, secured, upgraded, troubleshot, and owned production EKS environments end-to-end.

This is not an application development role with some DevOps exposure, nor is it primarily a people-management position. The successful candidate must have a strong track record in core DevOps / Platform Engineering and remain deeply hands-on technically.

You will help define the DevOps roadmap, establish platform standards and reusable patterns, improve infrastructure automation and reliability, support application releases, and provide production support for critical workloads.

The role will also contribute to the practical adoption of AI within DevOps and infrastructure engineering, including AI-assisted Infrastructure as Code (IaC), automation, runbooks, operational workflows, incident response, and platform tooling.

Critical Screening Requirements

This is not an application developer position with some DevOps exposure. We require someone whose core professional background demonstrates substantial, hands-on DevOps / Platform Engineering experience, particularly with AWS and production Amazon EKS.

The resume must provide concrete project-level evidence, not simply keywords. It should clearly demonstrate:

EKS environments the candidate personally designed, built, and owned end-to-end
Cluster architecture, lifecycle management, upgrades, networking, security, and troubleshooting responsibilities
Terraform/IaC solutions the candidate personally designed or implemented
Platform standards, reusable modules, guardrails, frameworks, or engineering practices they established
Production incidents and complex infrastructure issues they personally troubleshot and resolved
Specific examples of applying AI to DevOps, infrastructure, automation, or platform engineering
Evidence of technical/platform leadership while remaining hands-on

Simply listing AWS, Kubernetes, EKS, Terraform, DevOps, or AI in a technical skills section without concrete evidence of hands-on implementation and ownership will not be sufficient.

What We Need

Amazon EKS – End-to-End Ownership

Deep, hands-on experience with Amazon EKS in production environments
Proven experience personally designing, building, deploying, operating, upgrading, securing, monitoring, and troubleshooting EKS clusters
Strong Kubernetes architecture and operations expertise
Experience owning EKS environments throughout their full lifecycle
Strong knowledge of cluster networking, security, RBAC, IRSA, secrets, observability, capacity management, upgrades, and production troubleshooting
Experience resolving cluster-level production incidents, not simply application-level deployment issues

Candidates whose Kubernetes experience is primarily limited to deploying applications onto clusters managed by another team will not meet the core requirement.

AWS & Infrastructure as Code

Strong hands-on AWS infrastructure experience, including multi-account and multi-environment architectures
Advanced experience with Terraform; Terragrunt experience is highly desirable
Experience designing reusable IaC modules and environment-driven infrastructure
Strong understanding of AWS networking, IAM, security, secrets, encryption, tagging, and infrastructure guardrails
Experience with infrastructure automation, reliability, observability, and production support
Strong incident management, root-cause analysis, and troubleshooting capabilities

Platform Engineering & Technical Leadership

Proven experience establishing DevOps/platform standards, tooling, frameworks, guardrails, and engineering practices
Ability to define how infrastructure should be built, deployed, secured, monitored, and operated
Experience creating reusable IaC modules, CI/CD standards, automation frameworks, runbooks, reference architectures, and platform patterns
Experience conducting technical/design reviews and influencing DevOps or platform roadmaps
Ability to provide technical leadership while remaining strongly hands-on

AI for DevOps / Infrastructure

We are looking for demonstrated practical exposure to applying AI within DevOps, cloud infrastructure, or platform engineering, such as:

AI-assisted Terraform/IaC authoring and review
AI-assisted pipeline and automation development
Infrastructure/platform automation
Operational documentation and runbook creation or improvement
Incident summarization, troubleshooting, and triage
Internal tooling for infrastructure or platform teams
Evaluation and adoption of AI coding assistants or platform tools
Internal LLM/RAG solutions for operational knowledge

Candidates should understand the importance of verification, security, compliance, governance, and change control when using AI in production environments.

Key Responsibilities

Define and drive DevOps priorities across security, reliability, cost, scalability, and delivery velocity
Establish AWS standards, guardrails, and reusable patterns across networking, identity, secrets, tagging, and infrastructure
Design, implement, and review infrastructure using Terraform and Terragrunt
Build and own Amazon EKS environments end-to-end, including:
Cluster architecture, creation, and lifecycle management
Version upgrades and patching
Node groups and capacity management
VPC/CNI, DNS, ingress, and networking
RBAC, IRSA, secrets, and security controls
Add-ons and cluster baseline tooling
Monitoring, logging, tracing, and observability
Performance, reliability, and cost optimization
Production troubleshooting and cluster-level incident resolution
Develop and maintain CI/CD pipelines and safe promotion processes across development, non-production, and production environments
Work with AWS services including RDS/Aurora, DynamoDB, S3, CDN, KMS, Secrets Manager, SNS, Lambda, and EventBridge
Support IAM, VPC, and multi-account/multi-environment AWS architectures
Partner with development teams on releases, deployment strategies, rollbacks, and post-release validation
Participate directly in production incident response, root-cause analysis, and preventive remediation
Improve monitoring, alerting, dashboards, operational documentation, and runbooks
Partner with security, architecture, and engineering teams on least-privilege access, encryption, backup/DR, and audit-ready operations
Identify practical opportunities to use AI to improve infrastructure engineering and operational efficiency

Required Qualifications

6+ years of experience across DevOps, SRE, Platform Engineering, Systems Engineering, or related infrastructure-focused roles
4+ years of hands-on AWS production experience
Deep Amazon EKS expertise – mandatory
Demonstrated experience personally building and owning production Kubernetes/EKS environments
Strong hands-on experience with Terraform and modular Infrastructure as Code
Strong knowledge of Kubernetes networking, security, RBAC, IRSA, secrets, observability, capacity management, and production troubleshooting
Strong understanding of CI/CD, artifact promotion, secrets injection, and multi-environment deployment practices
Experience responding directly to production incidents, conducting RCAs, and implementing long-term remediation
Experience establishing technical standards, conducting design reviews, and contributing to DevOps/platform roadmaps
Demonstrated experience or strong practical exposure to AI-assisted DevOps or platform engineering
Excellent communication skills and ability to collaborate across engineering, security, architecture, and development teams

Preferred Qualifications

AWS Solutions Architect – Professional or AWS DevOps Engineer – Professional
CKA or CKS certification
Terragrunt experience
Helm / Helmfile experience
Policy-as-code and Kubernetes cluster baseline tooling
PostgreSQL / AWS RDS experience
Experience in regulated, enterprise, or other high-stakes production environments
Experience defining SLOs, error budgets, or platform KPIs
AWS cost optimization / FinOps exposure
Experience with AI coding assistants, internal LLM/RAG solutions, or AI-enabled platform operations

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More about this job

Responsibilities

Own and evolve production AWS infrastructure, including designing, building, securing, upgrading, and troubleshooting Amazon EKS clusters and Terraform-based infrastructure. Establish platform standards and automation, support CI/CD and production operations, resolve incidents, and identify practical applications of AI in infrastructure engineering.

Requirements

Requires at least 6 years of infrastructure-focused experience, 4 years of hands-on AWS production experience, and deep personal ownership of production EKS environments. Candidates must demonstrate strong Terraform, Kubernetes operations, incident response, platform leadership, and practical exposure to AI-assisted DevOps.

Skills

Amazon EKS
AWS
Kubernetes
Terraform
Terragrunt
Infrastructure as Code
Platform Engineering
DevOps
CI/CD
AWS Networking
IAM
Incident Response
Root-Cause Analysis
AI-Assisted DevOps
Observability
Production Troubleshooting

Visa sponsorship

Not detected in the job text

Keywords

AWS
Amazon EKS
Kubernetes
Terraform
Terragrunt
Helm
Helmfile
Infrastructure as Code
Platform Engineering
DevOps
SRE
CI/CD
Multi-Account Architecture
AWS IAM
VPC
RBAC
IRSA
Secrets Manager
KMS
RDS
Aurora
DynamoDB
S3
Lambda
EventBridge
Policy as Code
Observability
Incident Response
Root-Cause Analysis
AI-Assisted Infrastructure Engineering

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