Site Reliability Engineer II

You will:

Manage multiple cloud accounts—primarily AWS today—using tools like AWS Control Tower and Terraform, with a growing focus on GCP as we build out that practice

Debug system issues, identify bottlenecks, and improve system health—utilization, performance, and reliability—across our infrastructure

Understand how systems fail and work with the team to reduce that risk, identifying toil and automating it away

Design, build, and maintain production-quality software—with tests, documentation, and code review—that automates reliability engineering work:

Deployment tooling

Fault-injection/chaos harnesses

Capacity planning

Observability pipelines

Identify optimal cloud solutions and maintain infrastructure per industry standards

Participate in an on-call rotation as part of a follow-the-sun model (12-hour shifts approximately every 5 weeks)

You have:

3+ years Linux/UNIX systems administration experience

3+ years Google Cloud Platform (GCP) experience — IAM, VPC, GKE, Cloud Monitoring/Logging, or equivalent

Experience provisioning public cloud resources using Infrastructure-as-Code frameworks such as Terraform

Server configuration experience with Ansible / Puppet / Chef / Salt

Git team environment experience, including code reviews of production code

Experience designing and building services or internal tools, with solid grounding in data structures, algorithms, and distributed systems fundamentals — including scripting/automation work (Python, Go, or Bash) for operational tooling

Experience troubleshooting full-stack applications (client/load balancer/frontend/backend/DB) and using the right tools to dig into issues at each layer

You'll have an advantage if you have experience with:

AWS, including Control Tower and Terraform. You'll ramp up on our primary cloud environment with support from the team.

Professional experience building with AI coding assistants or agentic tooling (e.g., Claude Code, Gemini, LLM-based automation), not just casual chatbot use.

Experience building automation or agent-based workflows for operational use cases — alert correlation, incident summarization, fault-injection/test scenario generation.

Familiarity with Model Context Protocol (MCP) or similar tool-integration patterns for AI agents

Docker and Kubernetes

DevOps automation platforms like Jenkins and Artifactory

Monitoring solutions development across multiple cloud providers

Compensation Range: CAD 87,000 – 105,000

In accordance with Pay Transparency Act the approximate compensation range for this role in Canada is listed above. Final compensation for this role will be determined by various factors, such as knowledge, skills, and abilities.