
Posted 1 month ago
(Canada) - Junior Site Reliability Engineer
AI Summary
A Junior Site Reliability Engineer monitors and improves production system reliability, responds to incidents, and drives automation and AI‑driven observability initiatives.
About this role
Job Summary:
The purpose of this role is to help monitor, improve, and engineer production systems so they are reliable and meet client expectations. The Site Reliability Engineer works to ensure services operate smoothly, quickly restore service during incidents, and minimise customer impact. When issues occur, the role focuses not only on resolution but also on identifying root causes and driving improvements to prevent incidents from recurring. This role is critical to delivering a stable, high quality experience for PointClickCare clients.
Reporting to the Sr Manager, Applications Operations Engineering
Key Responsibilities:
• Participate in incident response and supported on‑call practices, helping restore service quickly while documenting incidents and recovery actions.
• Design, implement, and maintain monitoring and observability solutions, including dashboards, alerts, logs, metrics, and traces, to understand system behavior and proactively improve reliability.
• Engineer and enhance AI‑driven anomaly detection and root cause analysis solutions to continuously improve system reliability and prevent repeated failures.
• Contribute to automation and AIOps initiatives, including scripting, event driven workflows, and AI assisted runbooks that reduce manual effort and operational toil.
• Continuously develop Site Reliability Engineering skills through mentorship, hands on production exposure, and application of SRE best practices.
Your Key Strengths:
• 2 years of relevant experience or co-op/internships as a Software Engineer
• Monitoring or logging familiarity with Appdynamics, DataDog, ELK/Kibana or similar tools.
• Basic scripting or programming skills (Python, Bash and Java)
• Hands on experience deploying, operating, or supporting containerized workloads using Kubernetes and Docker.
• Demonstrates curiosity, continuous learning, and a growth oriented mindset.
• Experience with cloud native infrastructure and platforms such as Azure or AWS.
• Ability to collaborate effectively
• Experience working with Agentic AI and LLM based solutions used to support automation.
Skills
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