Hiring.Camp

Principal AI Engineer

Pointclickcare

·

Today

Salary
C$192k – C$213k/yr
Location
Mississauga
Workplace
Hybrid
Type
Full-time
Department
PointClickCare
Seniority
Lead
Experience
8+ years
Source
Lever

Description

At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.

With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work. 

At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.

Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out 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 Agentic Platform team operates at the leading edge of AI technology. We continuously evaluate emerging services, frameworks, and capabilities — identifying which ones PointClickCare should adopt to unlock AI-powered products that serve our customers across senior care and beyond. The team owns the agentic platform end to end. We identify and build scalable platform capabilities and codify playbooks and patterns that accelerate implementation across the organization. Through close collaboration with product, engineering, and operations teams, we transform promising prototypes into production-ready solutions. We also invest deeply in talent development, equipping teams across PointClickCare with the skills and tools to embed AI into PointClickCare’s products.
 
Job Summary:
 
The Principal AI Engineer will design and architect scalable, secure, and enterprise-grade AI/ML platforms and solutions that enable product teams to rapidly build and deploy AI applications. Working at the intersection of product strategy and technical implementation, the Principal AI Engineer will define architectural patterns, establish technical standards, and guide engineering teams in building cloud-native AI infrastructure that aligns with organizational goals. The Principal AI Engineer will create reference architectures, evaluate emerging AI technologies, and ensure alignment between AI platform capabilities and product roadmap requirements.
 
Key responsibilities:
  • Design and document enterprise AI platform architectures including reference implementations for agentic systems, RAG pipelines, and multi-modal AI applications with integrated guardrails, observability, and security patterns
  • Define and maintain architectural standards, design patterns, and best practices for GenAI infrastructure including model serving, prompt management, vector storage, evaluation frameworks, and LLMOps pipelines.  
  • Lead technical evaluations and vendor assessments for AI infrastructure components (model gateways, vector databases, observability tools) and provide architectural recommendations aligned with organizational requirements.  
  • Collaborate with product, engineering, and platform teams to translate business requirements into scalable AI architectural solutions, ensuring consistency across multiple product implementations.  
  • Establish architectural governance for AI/ML workloads including security controls, compliance frameworks, cost optimization strategies, and multi-cloud deployment patterns (Azure, AWS).  
 
Preferred Qualifications:
 
  • Experience with Azure OpenAI Service, Azure AI Studio, and Azure Machine Learning platforms in healthcare or regulated industries  
  • Familiarity with observability frameworks for AI systems (OpenTelemetry, MLFlow, Arize, LangSmith) and production monitoring strategies  
  • Understanding of healthcare compliance requirements (HIPAA, PHIPA) and security frameworks for AI applications  
  • Experience with Infrastructure as Code (Terraform, Bicep) and GitOps practices for AI platform automation  
Minimum Qualifications:
 
  • 8+ years of experience in cloud architecture and platform engineering with AWS and/or Azure, with at least 3+ years focused on AI/ML infrastructure and GenAI solutions 
  • Proven track record designing and implementing enterprise-scale AI/ML platforms supporting multiple product teams and use cases  
  • Deep expertise in cloud-native architectures including microservices, event-driven systems, serverless patterns, and container orchestration (Kubernetes)  
  • Strong understanding of GenAI architectural patterns including RAG, agentic frameworks (LangGraph, CrewAI), prompt engineering, and LLM evaluation methodologies  
  • Experience with AI infrastructure components such as vector databases (Pinecone, Weaviate, pgvector), model serving platforms (vLLM, SGLang, Azure AI), and prompt management systems  
#LI-AV1
#LI-Hybrid

Skills

AWSAzureKubernetesTerraformMachine LearningMicroservicesComplianceHIPAA

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