Lead DevOps Engineer

Location: Oakville, Ontario (Hybrid - 2 days/week onsite) About the role We are seeking two highly skilled and experienced Lead DevOps Engineers to join a modern, complex, and high-growth AWS cloud environment. This is a hands-on technical leadership role focused on deep technical contribution, project ownership, and providing mentorship—it does not involve people management. You will be a key driver in evolving our cloud infrastructure and CI/CD pipelines as we transition from a Kubernetes-centric platform toward a serverless architecture. If you thrive on tackling complex, large-scale cloud challenges and are passionate about IaC, automation, and cutting-edge AWS services, this is the role for you. Key Note: If you feel you are a match to the qualifications and experience listed for this position, please do feel free to send your up-to-date CV directly to . Due to the highly specialized nature of this role, only candidates who meet the following mandatory technical requirements will be contacted: Extensive hands-on AWS experience (Azure-only candidates will not be considered). Strong expertise in Kubernetes (configuration, troubleshooting, management). Proven experience with Terraform, including writing code and managing state files. Proficiency with Unix/Linux command-line tools. 5+ years of relevant DevOps/Cloud Engineering experience Please ensure your resume clearly reflects these skills and experience levels. What You Will Be Doing As a technical leader within the DevOps team, your time will be split approximately 75% on hands-on technical work and operational support and 25% on research, learning, and future technology exploration. Cloud Architecture & IaC Leadership: Serve as the subject matter expert for our fully migrated AWS cloud environment (64+ accounts), championing best practices for stability, design, and implementation. Drive and manage the adoption of Infrastructure as Code (IaC), including advanced use of Terraform (writing, deploying, and managing state files) across our complex infrastructure. Lead the transition of workloads from VMs to Kubernetes (EKS) and ultimately toward AWS Lambda/Serverless. Automation & CI/CD Mastery: Maintain and enhance our Git-based CI/CD pipelines (GitLab currently, with experience in GitHub or Jenkins being relevant) and associated tooling (e.g., Artifactory, SonarQube). Contribute to the configuration and management of over 55+ AWS services, including EKS, Lambda, Sagemaker (MLOps), Kafka/MKS, and various database/data services. Operational Excellence & Security: Provide technical mentorship and direction to other DevOps engineers and IT team members. Lead discussions and implementation for IAM and configuration management strategies (e.g., AWS IAM Identity Center). Take part in an on-call rotation (approximately one week every five weeks) and perform occasional late-night deployments with time off in lieu. Required Technical Expertise We are looking for candidates who can demonstrate deep, hands-on proficiency in a Linux-based environment. Only candidates with extensive AWS expertise will be considered. Cloud Platform: Extensive, hands-on experience with AWS (Azure-only candidates are not a fit). Containerization: Strong expertise in Kubernetes (EKS), including configuration, troubleshooting, and cluster management. Infrastructure as Code: Proven, hands-on experience with Terraform, including writing modular code and managing state files in production. Operating System: High proficiency with Unix/Linux command-line tools for scripting, automation, and deep troubleshooting (e.g., bash). Source Control/CI: Solid experience with CI/CD systems and source control (GitLab preferred; experience with GitHub, Jenkins, or Bitbucket is acceptable). Preferred Qualifications & Bonus Skills Certifications: Professional-level AWS certifications (e.g., AWS Solutions Architect Professional, AWS DevOps Engineer Professional). Tooling: Experience with cloud-native deployment tools such as Argo CD, Helm charts, or Carpenter. Education: Bachelor’s degree in Computer Science or a related technical field is an asset. Domain: Exposure to AI/MLOps tooling or novel database technologies.