Site Reliability Engineer

\"We are searching for an exceptional Site Reliability Engineer to join our growing engineering team This role is perfect for someone passionate about architecting scalable cloud infrastructure, maintaining Kubernetes clusters, building robust CI/CD pipelines, and establishing comprehensive observability to ensure our platforms and internal services remain reliable, performant, and resilient. Looking forward to seeing how you\'ll help drive our engineering operational excellence forward\"

– Greg Burlet, Director of Engineering

About Amii

Alberta Machine Intelligence Institute (Amii) is one of Canada\'s three main institutes for artificial intelligence (AI) and machine learning, our world-\renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world\'s top scientific talent. Our cross-\functional teams work collaboratively with Alberta-\based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

About The Role

The Site Reliability Engineer (SRE) plays a key role in ensuring that production applications, infrastructure, and internal services remain reliable, performant, and scalable. As a core technical team member, the SRE collaborates with both the Engineering and IT teams to manage cloud infrastructure, build robust CI/CD and deployment automation, maintain Kubernetes clusters, and establish comprehensive monitoring, alerting, and incident management workflows. Crucially, this role is responsible for ensuring that internal services created by the Engineering team for both intracompany and external use operate reliably and scale seamlessly according to demand.

The Site Reliability Engineer will focus on improving system availability, resilience, performance, and operational efficiency across all hosted services and infrastructure. This role spans production operations, infrastructure-as-code, deployment automation, capacity planning, budget management, and observational tooling. A central purpose of the role is to guarantee that internal platforms and services developed by the Engineering team, whether serving internal Amii staff or external customers, run with high availability, meet defined SLAs/SLOs, and automatically or efficiently scale to meet fluctuating user demand.

In addition to day-to-day operations and incident response, the Site Reliability Engineer will partner with the Director, Engineering to establish reliability best practices, budgets, disaster recovery playbooks, infrastructure automation standards, and scalable cloud architectures across the organization.

The position focuses on achieving excellence in three main accountabilities:

• Infrastructure Reliability & Internal Service Scaling
• Observability, Automation & Incident Management
• Reliability Coaching & Operational Excellence

Required Skills / Expertise

Key Responsibilities

• Ensures all internal and external services created by the Engineering team run with high availability, resilience, and automatically/dynamically scale based on traffic and demand.
• Architects and manages containerized workloads on Kubernetes clusters (EKS/GKE) and cloud infrastructure using Infrastructure-as-Code (Terraform).
• Designs, implements, and maintains robust CI/CD pipelines to enable continuous, automated, and zero-downtime deployment of microservices and internal tools.
• Contributes to development of CI/CD pipelines and ansibles for bare-metal deployments.
• Conducts capacity planning, load testing, auto-scaling configurations, and performance tuning across cloud networks, databases, and API gateways.
• Implements automated disaster recovery, backup, and failover mechanisms across critical production and non-production systems.
• Participates in sprint planning and other agile methodology ceremonies.
• Establishes comprehensive observability frameworks (Prometheus, Grafana, etc.) for real-time monitoring, metrics, log aggregation, and tracing.
• Defines, tracks, and enforces Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Error Budgets for internal and external platform services.
• Leads on-call rotations, incident response, root cause analysis (RCA), and blameless post-mortems to continuously improve system resilience.
• Automates operational toil, security patching, certificate management, and system maintenance using scripts and infrastructure tools.
• Monitors and optimizes AI workload infrastructure (e.g., vector database hosting, model inference serving, compute GPU/CPU utilization) for stability and cost efficiency.
• Collaborates with product management and AI researchers to translate complex AI models into scalable software products.
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