Principal AI Engineer

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