Senior Site Reliability Engineer, AI Infrastructure

PointClickCare•Mississauga, ON

2d•CA$139,000 - CA$155,000•Remote

About The Position

At PointClickCare, we are a leading health tech company dedicated to helping providers deliver exceptional care. As a founder-led and privately held organization, we empower our employees to innovate and shape the future of healthcare. With the largest long-term and post-acute care dataset and a vast Marketplace of integrated partners, our platform impacts millions of lives by serving over 30,000 provider organizations. We reinvest significantly in research and development, providing our employees with the resources needed for innovation and lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada's Most Admired Corporate Cultures, we offer a flexible, growth-oriented environment with meaningful work. We empower our people to be architects of a smarter, human-first healthcare future, accelerated by AI. Employees harness AI as a catalyst for creativity, productivity, and informed decision-making, enhancing collaboration, improving outcomes, and maximizing individual impact. Our hiring practices focus on uncovering AI expertise that aligns with our mission, and we continuously invest in training and development to foster innovation throughout the employee journey. Join us in redefining healthcare so it doesn’t just survive, it thrives. To learn more about PointClickCare, explore Life at PointClickCare and connect with us on Glassdoor and LinkedIn. Travel to Office expectations: For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings. For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. Team Summary: The AI SRE team is a focused group of SRE engineers dedicated to making PointClickCare's AI and ML platforms reliable, secure, and operationally excellent — from data processing and ML workspaces to model serving and labeling systems. We treat reliability as a product — prioritizing observability, automation, and safe operations so that data scientists and ML engineers can focus on building AI capabilities that improve patient care. You will spend a significant portion of your time hands-on — building automation, designing guardrails, hardening platforms, and leading incident response across cloud environments like Databricks, Azure AI suites. The team collaborates closely with research, platform, data, and security teams across the AI engineering organization. Job Summary: AI SRE exists to ensure PointClickCare's AI platforms run safely, reliably, and efficiently — protecting patient data while enabling teams to move fast with confidence. We solve complex cross-cutting reliability and security problems through well-designed automation, SLOs, and operational guardrails — so that product and research teams can focus on delivering AI-driven value to clinicians and patients. We own the infrastructure operability of AI data processing, ML workspaces, labeling systems, and model serving — and we drive the infrastructure observability, incident response, compliance controls, and cost optimization that keep those platforms healthy through sound SRE practices and a security-first mindset.

Requirements

5+ years in SRE, platform engineering, or infrastructure roles supporting production cloud environments and mission-critical applications
Strong proficiency with observability — metrics, logging, distributed tracing, SLI/SLO frameworks — and production ownership including incident response, blameless postmortems, and on-call operations
Strong proficiency with Infrastructure as Code (Terraform), GitOps practices, and CI/CD for infrastructure and platform changes
Working proficiency with cloud platform administration — compute, networking, storage, and operating managed data or AI/ML platform services in production (e.g., Databricks, Azure ML, or Kubernetes-hosted infrastructure)
Working proficiency with platform security — network segmentation, secrets management, encryption at rest and in transit, and key management
Strong programming skills for automation, operational tooling, and infrastructure management
Strong communication and documentation skills — able to write runbooks, lead postmortems, influence operational standards across teams, and translate technical complexity for diverse audiences

Nice To Haves

Experience with disaster recovery planning, multi-region patterns, and capacity or cost optimization (FinOps)
Working knowledge of container orchestration (Kubernetes), progressive delivery patterns (blue/green, canary), and data lineage tooling
Experience in healthcare, life sciences, or other highly regulated industries with data privacy requirements

Responsibilities

Own service level objectives, error budgets, and reliability targets for the infrastructure underpinning cloud-based platforms — ensuring infrastructure observability (metrics, logs, traces), alert quality, and telemetry completeness across platform components and serving endpoints
Design, build, and maintain infrastructure-as-code, operational automation, and change control workflows for AI/ML platforms — with a focus on repeatability, consistency, and toil reduction
Implement and maintain platform security controls — including network segmentation, secrets management, encryption, and data protection safeguards — aligned to compliance requirements and partnering with security teams to respond to emerging risks
Lead incident response and blameless postmortems; validate backup/restore and disaster recovery processes; conduct game days and resiliency testing to harden platform and infrastructure reliability
Mentor engineers, influence design reviews, and collaborate across engineering teams to improve platform resiliency, cost efficiency, capacity planning, and operational standards