Senior Data & AI Platform Engineer

RBC; Vancouver; On-site; CAD 120,000 - 180,000; Full time

Job summary

RBC is seeking a Senior or Staff Data/AI Engineer to strengthen the Commercial Credit data and AI foundation. You will design scalable data pipelines, feature stores, and governance patterns for credit decisioning and risk modeling, collaborating with ML researchers and cross-functional partners.

You will own end-to-end ML systems in production, drive DataOps/MLOps automation, and mentor teammates while aligning with RBC's data strategy.

Qualifications

• Bachelor's degree in CS/Software Eng plus significant data/ML/AI experience.
• Strong SQL skills across relational and NoSQL systems.
• Proficiency in production-grade coding with testing and code-review practices.
• Deep expertise in data modeling, distributed systems, storage optimization for large-scale AI workloads.
• Experience owning end-to-end ML systems in production (feature stores, model serving, data pipelines).

Responsibilities

• Design and optimize data models, feature stores, and storage patterns for governance and performance.
• Build and maintain scalable batch and streaming data pipelines for AI workloads.
• Implement DataOps and MLOps automation, including CI/CD, data validation, and model deployment.
• Write production-quality code, review others' work, and improve system reliability.
• Lead shared data/ML platform capabilities serving multiple teams and use cases.
• Coordinate with policy/risk teams and client teams while preserving data integrity.
• Document designs and reference architectures to align with RBC data strategy.
• Mentor engineers and set technical direction for complex data/AI problems.

Skills

Data Modeling

Distributed Systems

SQL

ML Engineering

Software Engineering

CI/CD

Education

Bachelor's degree in CS/Software Engineering

Tools

Python

Git

CI/CD

Job description

RBC is seeking a Senior or Staff Data/AI Engineer to strengthen the Commercial Credit data and AI foundation. You will design scalable data pipelines, feature stores, and governance patterns for credit decisioning and risk modeling, collaborating with ML researchers and cross-functional partners.

You will own end-to-end ML systems in production, drive DataOps/MLOps automation, and mentor teammates while aligning with RBC's data strategy.