Shape RBC’s AI-DLC Platform with LLMOps, RAG, evaluation frameworks, and protected production delivery across governed software development.

This Principal AI Engineer will establish the platform architecture, runtime, standards, and pipelines supporting AI-assisted delivery. The mandate includes model lifecycle management, cost and latency optimization, context management, observability, reliability, and auditable code promotion. You will partner with Risk, Engineering, senior leadership, and cohort teams.

Key Responsibilities:

- Define platform standards, runtime architecture, and technical roadmap
- Establish LLMOps, evaluation, governance, RAG, and optimization practices
- Build monitoring distinguishing model, code, and platform failures
- Engineer rollback, circuit breakers, degradation,



and zero-downtime deployment
- Present architecture, progress, impact, and direction to executives

Requirements:

- Deep prompt engineering and model lifecycle management experience
- Expertise in RAG, context management, and evaluation frameworks
- Mastery of CI/CD, Docker, Kubernetes, and infrastructure-as-code
- Experience with AWS, Azure, GCP, or enterprise platforms
- Background building scalable automated testing and validation

Apply LLM engineering, platform architecture, evaluation, and reliability expertise to RBC’s governed AI-DLC delivery foundation.

📌 Principal AI Platform Architect LLMOps (Toronto)
🏢 RBC
📍 Toronto