Senior Site Reliability Engineer, AI Infrastructure

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

Key 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

Qualification and Skills:

Minimum:

• 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

Preferred:

• 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
• 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