Job Description
What is the opportunity?
As a Staff Engineer within RBC Borealis' Lumina Production Engineering team, you will be responsible for providing expert-level support for critical systems and services, you will also serve as a technical leader responsible for developing and maintaining the critical infrastructure that powers RBC's next-generation AI and innovation platforms.
The role demands strong problem-solving capabilities, architectural thinking, and the ability to mentor technical teams while managing high-impact incidents.
This is an ideal fit for experienced technical professionals seeking to leverage their expertise in a fast-paced, innovative environment while driving operational excellence across RBC's AI infrastructure.
Production Engineers at RBC Borealis build the foundational systems that enable every major innovation initiative within Lumina's portfolio. Working alongside industry-leading engineers within RBC's innovation hub, you'll contribute to code and systems that directly power breakthrough AI capabilities, advanced analytics platforms, and next-generation customer experiences.
What will you do?
Production Infrastructure Ownership
Own and operate backend services that power Lumina's AI/ML platforms, real-time analytics engines, and experimental customer-facing applications
Operate the infrastructure components and provide tier 3 and 4 technical support that drive RBC Borealis' advances in artificial intelligence, machine learning, and data science initiatives
Manage core services including large-scale data processing pipelines, model serving infrastructure, feature stores, and high-throughput API gateways
Partner with innovation teams to ensure seamless integration of experimental technologies into RBC's enterprise architecture
Technical Leadership & Engineering Excellence
Lead engineering initiatives by example, mentoring team members and driving technical excellence across Borealis innovation projects
Write, review, and optimize code that operates at enterprise scale within fast-moving innovation cycles
Develop comprehensive documentation, capacity planning models, and operational runbooks for rapidly evolving systems
Debug complex production issues live on cutting-edge AI/ML infrastructure and experimental platforms
Operational Excellence & Incident Response
Participate in on-call rotations and serve as an escalation contact for critical service incidents affecting Lumina's innovation platforms
Drive post-incident reviews and implement systematic improvements to prevent recurrence in rapidly evolving systems
Partner with stakeholder teams to establish and maintain service level objectives (SLOs) for experimental and production AI workloads
Champion proactive monitoring, alerting, and automated remediation strategies for novel technology stacks
Cross-Functional Collaboration
What do you need to succeed?
Must have:
7+ years of experience in production engineering, platform engineering, or similar roles supporting large-scale distributed systems or AI/ML platforms
Proficiency in at least one of: Python, Go, or another high level programming language with demonstrated experience building production services that support data-intensive workloads
Experience with container orchestration platforms (Kubernetes, OpenShift) and cloud-native architectures, particularly for AI/ML workloads
Deep understanding of both analytical and transactional data stores from a data engineering platform perspective (e.g., PostgreSQL, MongoDB, Elasticsearch, Kafka, Redis, vector databases)
Experience with CI/CD pipelines, infrastructure-as-code (Terraform, Ansible), and GitOps workflows supporting rapid iteration cycles
Proven track record of operating mission-critical systems with high availability requirements in dynamic, fast-paced environments
Experience with modern observability tools (Prometheus, Grafana, ELK stack) and distributed tracing for complex data pipelines
Solid understanding of networking fundamentals, load balancing, and content delivery networks supporting high-throughput applications
Bachelor’s degree in computer science, Engineering, or equivalent practical experience
Preferred Qualifications:
Experience supporting AI/ML infrastructure, model serving platforms, or data science workloads in production
Knowledge of enterprise governance, compliance frameworks, and regulatory requirements in innovation contexts
Experience with event-driven architectures, streaming data platforms, and real-time analytics systems
Understanding of capacity planning and performance optimization for GPU , CPU workloads and high-throughput data processing
Previous experience with incident management processes and on-call responsibilities in rapidly evolving technical environments
Experience in financial services, fintech, or other innovation-focused technology organizations
Advanced degree in Computer Science, Data Engineering, or related technical field
What makes you stand out:
Track record of leading technical initiatives that improved reliability and performance of AI/ML or data-intensive systems
Experience mentoring engineers in fast-paced innovation environments and contributing to technical community growth
Demonstrated ability to balance technical debt reduction with rapid feature delivery and experimentation
Strong communication skills with ability to influence both technical and business stakeholders in an innovation context
Passion for automation, eliminating manual operational overhead, and enabling developer productivity in AI/ML workflows
About RBC Borealis
RBC Borealis is the driving force behind Royal Bank of Canada’s AI and data innovation. As part of Canada’s largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we’re at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.
Inclusion and Equal Opportunity Employment
RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.
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Job Skills
Data Gathering Analysis, Effectiveness Measurement, Ethical Business, Fraud Management, Internal Controls, Long Term Planning, Process Management, Results-Oriented, Risk Management, Strategic ThinkingAdditional Job Details
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Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
Our Employment Opportunities
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
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