Infrastructure / Sre Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Infrastructure / SRE Engineer based in Canada.
As an Infrastructure / SRE Engineer, you will play a key role in designing, building, and maintaining the cloud infrastructure and reliability systems that support mission-critical software platforms. You will work across cloud environments, Kubernetes, infrastructure automation, deployment pipelines, and observability to ensure secure, scalable, and reliable production operations. Your mission will be to help engineering teams deliver software faster and more consistently while minimizing operational risks and manual workloads. You will take ownership of infrastructure as a product, developing repeatable solutions that improve performance, resilience, and cost efficiency. Working in a collaborative, client-facing environment, you will support complex enterprise deployments, including hybrid and customer-controlled environments. This is an opportunity to combine hands-on engineering, automation, and strategic problem-solving to strengthen the reliability of modern technology platforms.
Accountabilities:
Cloud Infrastructure and Platform Engineering:
Design, build, and operate scalable cloud infrastructure that supports production applications and enterprise platforms.
Develop and maintain cloud landing zones, networking configurations, identity management, security controls, and environment management processes.
Implement and manage infrastructure-as-code solutions to standardize provisioning, configuration, and infrastructure lifecycle management.
Build and maintain Kubernetes environments and containerized workloads to support reliable application deployment and operation.
CI/CD and Deployment Automation:
Develop and optimize continuous integration and continuous deployment pipelines to enable secure, consistent, and automated software delivery.
Establish repeatable deployment practices and infrastructure workflows that improve engineering efficiency and reduce operational complexity.
Support deployments across cloud, hybrid, Bring Your Own Cloud (BYOC), on-premises, customer-controlled, and edge environments.
Site Reliability and Observability:
Establish and maintain comprehensive observability capabilities, including metrics, logs, traces, dashboards, alerting, and actionable operational insights.
Define and support Service Level Objectives (SLOs), reliability standards, production readiness practices, and operational performance monitoring.
Lead or contribute to incident response, troubleshooting, root cause analysis, postmortems, and on-call operations.
Identify potential reliability risks and implement improvements that strengthen system availability, resilience, and performance.
Automation and Operational Excellence:
Automate repetitive operational tasks through scripting, internal tools, runbooks, and reusable platform services.
Reduce manual workloads and operational toil while improving deployment consistency and engineering productivity.
Develop standardized infrastructure capabilities that can be reused across multiple teams, products, and customer environments.
Cost and Capacity Optimization:
Monitor infrastructure usage, resource consumption, and system capacity to identify opportunities for optimization.
Improve infrastructure cost efficiency, particularly for resource-intensive environments involving GPUs and other specialized computing workloads.
Balance performance, scalability, reliability, security, and infrastructure costs when making technical decisions.
Customer and Cross-Functional Collaboration:
Collaborate with engineering teams, platform specialists, and client stakeholders to understand infrastructure requirements and deliver effective solutions.
Provide technical guidance and support for complex customer deployments, including regulated, air-gapped, hybrid, and mission-critical environments.
Contribute to infrastructure architecture decisions and help teams prepare applications for reliable production operation.
Use AI-assisted development tools where appropriate while maintaining rigorous standards for code quality, testing, security, and operational reliability.
Requirements:
Demonstrated professional experience building and operating production cloud infrastructure, with direct responsibility for system reliability and operational performance.
Strong expertise in infrastructure-as-code, including cloud landing zones, networking, identity and access management, security, and environment configuration.
Hands-on experience with Kubernetes, containerized applications, CI/CD pipelines, and automated deployment practices.
Strong understanding of observability practices, including metrics, centralized logging, distributed tracing, dashboards, alerting, and operational monitoring.
Experience defining or supporting Service Level Objectives (SLOs), reliability engineering practices, incident management, postmortems, and on-call operations.
Proficiency in scripting and automation, with the ability to develop tools, runbooks, and reusable solutions that reduce manual operational work.
Experience managing cloud infrastructure and production environments, with a strong understanding of scalability, availability, performance, and security.
Knowledge of infrastructure cost management and capacity planning, including experience optimizing resource-intensive workloads such as GPU computing.
Familiarity with customer-controlled infrastructure, hybrid cloud, Bring Your Own Cloud (BYOC), on-premises, or edge deployment environments is highly desirable.
Strong communication and collaboration skills, particularly when working with clients, technical stakeholders, and cross-functional engineering teams.
Ability to troubleshoot complex technical issues, make pragmatic architectural decisions, and balance delivery speed with operational safety and quality.
Comfortable taking ownership of production systems, working independently, and remaining composed when managing incidents or competing priorities.
Preferred Qualifications:
Experience with Microsoft Azure and infrastructure technologies such as Kubernetes, Terraform, and Bicep.
Familiarity with GitHub Actions, Azure DevOps, and modern CI/CD and infrastructure delivery tools.
Experience with Azure Arc, infrastructure fleet management, pull-based deployment models, and configuration or version drift management.
Previous experience supporting regulated, air-gapped, edge, or other mission-critical environments.
Exposure to AI/ML platforms, model-serving infrastructure, GPU workloads, or AI development lifecycle operations.
Experience building and maintaining enterprise-scale infrastructure supporting multiple products, customers, or engineering teams.
Familiarity with AI-assisted development tools and the ability to integrate them into engineering workflows without compromising code quality or operational discipline.
Benefits:
Permanent employment:
Secure, full-time employment with a globally established software organization.
Remote flexibility:
Work remotely from Canada, with the flexibility of a distributed working environment.
Competitive compensation:
Compensation details to be discussed during the recruitment process, based on experience and qualifications.
Enterprise-scale projects:
Work on sophisticated infrastructure and cloud engineering initiatives supporting mission-critical customer environments.
Modern technology stack:
Gain hands-on exposure to Azure, Kubernetes, infrastructure-as-code, automation, observability, and advanced cloud technologies.
Technical ownership:
Take responsibility for production infrastructure and influence important architectural and reliability decisions.
Professional development:
Expand your expertise in Site Reliability Engineering, cloud platforms, infrastructure automation, and AI/ML infrastructure.
Collaborative environment:
Work alongside experienced engineering professionals and client stakeholders in a technology-driven organization.
Meaningful impact:
Improve infrastructure reliability, reduce operational complexity, and help engineering teams deliver software more efficiently.
Continuous innovation:
Explore modern infrastructure practices and AI-assisted development technologies while contributing to scalable enterprise solutions.
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