Senior AI Engineer

TL;DR

Senior AI Engineer (AI Orchestration): Designing, building, operating and scaling the orchestration layer that powers AI-driven healthcare experiences with an accent on RAG pipelines, multi-step agents, and LLM-powered features. Focus on architecting production-grade AI systems, building evaluation frameworks, implementing MLOps practices, and ensuring scalability, observability, security, and compliance in a regulated environment.

Location: Remote from anywhere in Canada or US; Canada applicants only for stated compensation range. Toronto-area employees collaborate in-office Mon-Thu if within 65km of HQ.

$152,000 - $175,000 CAD

Company

Leading healthcare consumer experience (CX) platform powered by AI, reaching 63M+ people worldwide for payers, providers, and health partners.

What you will do

• Design and build production-grade AI systems including RAG pipelines, multi-step agents, and LLM-powered features; choose between RAG vs. fine-tuning and agentic vs. simple patterns.
• Build evaluation and observability frameworks, automated test suites, and LLM-as-judge pipelines to measure accuracy, grounding, and quality drift.
• Develop Python microservices wrapping AI logic, manage model lifecycle, prompts as code, and LLM economics for performance vs. cost/latency.
• Collaborate with Product, Data Science, and Backend teams; mentor juniors on AI practices; contribute to roadmaps and architecture.
• Establish standards for performance, security, privacy, and data governance in AI systems.

Requirements

• Deep expertise in software engineering and full ML lifecycle
• Experience designing scalable distributed systems for ML/data-intensive apps
• MLOps mastery: CI/CD for ML, model versioning, feature stores
• Cloud proficiency: GCP/AWS, Docker, Kubernetes
• Data fluency: pipelines, warehousing, distributed processing (Spark, Beam)
• Python expert; AI frameworks (TensorFlow, PyTorch, scikit-learn); MLOps tools (Kubeflow, MLflow, LangChain/LlamaIndex); Airflow; IaC (Terraform); relational/NoSQL DBs

Nice to have

• Go for backend services
• Vector databases (Pinecone, ChromaDB, Mongo) and retrieval strategies

Culture & Benefits

• AI-native organization: leverage AI tools daily for productivity with judgment and accountability
• Remote-eligible across Canada/US; flexible remote days quarterly; in-office collaboration Mon-Thu for Toronto-area
• Compensation exclusive of bonus, equity, benefits; career progression accounted in range
• Security responsibilities and compliance with policies

Hiring process

• Application review by recruiter (human); outreach if aligned
• Team-specific interviews shared by recruiter
• Reference and background checks prior to offer; additional for US candidates if applicable