Senior Platform & AI Systems Engineer

Codan Limited•Cana, CA

3d•CA$120,000 - CA$140,000•Hybrid

About The Position

Join our Mission: Zetron is part of the Codan group of companies and is an established global leader in connecting communication centers with field operations, personnel, and constituents. With offices in the US, UK, AU and CA, Zetron currently has a network of established partners, value-added resellers, and clients in more than 100 countries. Our Victoria, British Columbia office has been a center of engineering and manufacturing excellence since its founding in 1938. For over 80 years, we have been a trusted provider of LMR communication products and solutions that help our customers protect, inform, and save lives. Now we are applying those standards of excellence to build and deliver interoperable end-to-end command and control systems across multiple industries and international markets. With team members located across the globe, we work on platforms and products where reliability, security, and operational excellence are foundational, not optional. Always ready, always on! Role Responsibilities: Senior Platform & AI Systems Engineers design, build, and operate the shared cloud platforms, automation, and AI-enablement capabilities that serve the internal business worldwide. Working closely with Principal Engineers on platform design and independently delivering complex, well-scoped solutions and improvements across business units, Senior Platform & AI Systems Engineers also participate in operations ownership, including incident response and continuous reliability improvement as well as coordinate with business-unit DevOps and SRE teams to land shared capabilities in the field. Specifically, a Senior Platform & AI Systems Engineer, will: Platform Engineering and Cloud Infrastructure Design, implement, and operate cloud infrastructure supporting shared platforms and business-unit workloads, primarily on AWS with growing Azure and Nutanix footprints. Build and maintain platform components supporting Kubernetes (EKS), containers, and core cloud services, and own complex shared-platform components end-to-end, including their operational consequences. Implement infrastructure using Terraform, following established multi-account and landing-zone patterns and contribute to the evolution of shared platform architecture through design reviews and implementation work. Reliability and Operational Excellence Apply SRE principles to improve reliability, scalability, and operational maturity of shared services. Define and maintain SLIs and SLOs for platform components. Participate in incident response, root cause analysis, and post-incident reviews. Implement reliability improvements through automation, monitoring enhancements, and operational fixes. Security and Operational Safety (DevSecOps) Incorporate security best practices and secure-by-default patterns into infrastructure and platform designs and roll out code security, supply chain, and scanning tooling across business-unit codebases. Ensure platform components meet Codan’s security and compliance requirements. Work with security partners to address findings and improve platform security posture. CI/CD and Automation Build and maintain CI/CD pipelines using GitHub Actions, supporting the consolidation of source control onto GitHub Enterprise. Automate infrastructure provisioning, deployment, and operational tasks while improving deployment safety, repeatability, and auditability across teams. AI Enablement Use AI coding agents and assistants, including OpenAI Codex, Claude Code, or equivalent approved tools, as a routine part of daily engineering work. Contribute to the shared AI capabilities the team provides, such as consumption reporting, gateways, and reusable workflows, applying responsible-AI guardrails. Validate AI-generated outputs and help teammates adopt effective, safe practices. Observability and Operations Implement and maintain monitoring, logging, and alerting using tools such as Prometheus, Grafana, Datadog, Splunk, and CloudWatch. Ensure platform and application health is visible and actionable. Respond to operational alerts and participate in on-call rotations as they are established. Documentation and Collaboration Produce clear technical documentation, operational runbooks, and design notes. Contribute to enterprise standards and reference architectures. Collaborate with business-unit teams to support safe and reliable use of shared platforms. Mentor Platform and Associate Engineers through code reviews, pairing, and operational support.

Requirements

Bachelor’s or Master’s degree in a related field, or an equivalent combination of experience and education
Five or more years of experience in cloud engineering, platform engineering, SRE, or DevOps adjacent roles
Hands-on experience operating a major cloud (AWS or Azure) in production
Experience using Terraform for infrastructure-as-code
Production experience operating Kubernetes workloads
Experience building or maintaining CI/CD pipelines
Working familiarity with AI coding agents such as OpenAI Codex or Claude Code in day-to-day work
Demonstrated ability to own a complex component or service end-to-end with limited oversight
Experience participating in incident response and operational support
Strong communication skills and attention to documentation

Responsibilities

Design, implement, and operate cloud infrastructure supporting shared platforms and business-unit workloads, primarily on AWS with growing Azure and Nutanix footprints.
Build and maintain platform components supporting Kubernetes (EKS), containers, and core cloud services, and own complex shared-platform components end-to-end, including their operational consequences.
Implement infrastructure using Terraform, following established multi-account and landing-zone patterns and contribute to the evolution of shared platform architecture through design reviews and implementation work.
Apply SRE principles to improve reliability, scalability, and operational maturity of shared services.
Define and maintain SLIs and SLOs for platform components.
Participate in incident response, root cause analysis, and post-incident reviews.
Implement reliability improvements through automation, monitoring enhancements, and operational fixes.
Incorporate security best practices and secure-by-default patterns into infrastructure and platform designs and roll out code security, supply chain, and scanning tooling across business-unit codebases.
Ensure platform components meet Codan’s security and compliance requirements.
Work with security partners to address findings and improve platform security posture.
Build and maintain CI/CD pipelines using GitHub Actions, supporting the consolidation of source control onto GitHub Enterprise.
Automate infrastructure provisioning, deployment, and operational tasks while improving deployment safety, repeatability, and auditability across teams.
Use AI coding agents and assistants, including OpenAI Codex, Claude Code, or equivalent approved tools, as a routine part of daily engineering work.
Contribute to the shared AI capabilities the team provides, such as consumption reporting, gateways, and reusable workflows, applying responsible-AI guardrails.
Validate AI-generated outputs and help teammates adopt effective, safe practices.
Implement and maintain monitoring, logging, and alerting using tools such as Prometheus, Grafana, Datadog, Splunk, and CloudWatch.
Ensure platform and application health is visible and actionable.
Respond to operational alerts and participate in on-call rotations as they are established.
Produce clear technical documentation, operational runbooks, and design notes.
Contribute to enterprise standards and reference architectures.
Collaborate with business-unit teams to support safe and reliable use of shared platforms.
Mentor Platform and Associate Engineers through code reviews, pairing, and operational support.