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 roadmapEstablish LLMOps, evaluation, governance, RAG, and optimization practicesBuild monitoring distinguishing model, code, and platform failuresEngineer rollback, circuit breakers, degradation,



and zero-downtime deploymentPresent architecture, progress, impact, and direction to executivesRequirements: Deep prompt engineering and model lifecycle management experienceExpertise in RAG, context management, and evaluation frameworksMastery of CI/CD, Docker, Kubernetes, and infrastructure-as-codeExperience with AWS, Azure, GCP, or enterprise platformsBackground building scalable automated testing and validationApply LLM engineering, platform architecture, evaluation, and reliability expertise to RBC’s governed AI-DLC delivery foundation.#J-18808-Ljbffr

📌 Principal Ai Platform Architect Llmops (Toronto)
🏢 RBC
📍 Toronto