Senior Data/AI Engineer

RBC•Vancouver, BC

1d•Onsite

About The Position

RBC's AI Group is seeking a Senior or Staff Data/AI Engineer to join the Commercial Credit team and build the data and AI foundation that powers credit decisioning, risk modeling, and AI/agentic workflows for RBC's commercial banking clients. In this role, you will work alongside ML Developers, Researchers, and cross-functional partners to transform raw, unstructured commercial credit data into clean, reliable, governed datasets that power machine learning applications at scale. You'll design and optimize the pipelines, platforms, and storage patterns that turn complex credit data challenges into competitive advantages. This is a rare opportunity to shape a newly formed, high-impact function—setting technical direction, driving meaningful scale, and delivering solutions that directly influence how RBC serves its small business and commercial clients. If you're passionate about data and energized by the potential of AI, this is your chance to make a lasting impact.

Requirements

Bachelor's degree in Computer Science, Software Engineering, or a related technical field, plus significant experience in data, ML, or AI engineering.
Strong SQL and database fundamentals across relational and NoSQL systems.
Proficiency in production-grade coding with strong software engineering fundamentals including version control, testing, and code review practices.
Deep expertise in data modeling, distributed systems, storage optimization, and performance tuning for large-scale AI and analytics workloads.
Solid understanding of the ML data lifecycle, including feature engineering, model integration, deployment support, and monitoring/drift detection.
Demonstrated mastery of end-to-end ML system ownership in production environments (feature stores, model serving, data pipelines) at scale.
Excellent communication and collaboration skills; ability to translate complex business requirements into well-architected technical solutions across product, platform, and cross-functional teams.

Responsibilities

Design and optimize data models, feature stores, and storage patterns to ensure performance, reliability, and governance across commercial credit AI workloads.
Build and maintain scalable batch and streaming data pipelines that ingest, transform, and curate high-quality datasets for AI and agentic workflows.
Implement DataOps and MLOps automation, including CI/CD pipelines, data validation, ML model deployment, monitoring, and drift detection.
Write production-quality code, conduct thorough code reviews, troubleshoot performance issues, and continuously enhance system reliability, scalability, and observability.
Lead the design and delivery of shared data/ML platform capabilities that serve multiple downstream teams and credit use cases.
Drive cross-functional technical initiatives, coordinating with feature providers, policy/risk teams, and client teams while maintaining system integrity.
Ensure design and development solutions align to RBC's data and architecture strategy, with adequate technical documentation and reference material.
Impart knowledge, mentor engineers, and set technical direction for the team on complex data/AI engineering problems.