Staff Engineer - Agentic AI

Job Description

What's the opportunity?
We’re looking for a Staff Engineer with strong hands-on experience in agentic AI systems who will contribute to accelerating agentic AI adoption across RBC. This role offers the opportunity to build production-grade solutions, work collaboratively with Lines of Business teams, and develop deep expertise in the Borealis agentic AI platform.

At RBC Borealis, you’ll be joining a team that bridges Lines of Business with our cutting-edge Borealis agentic AI platform. You’ll work directly with business stakeholders, platform engineers, and technical teams to implement high-impact solutions while building your capability in emerging agentic technologies with guidance from our Principal Engineers.

Your responsibilities include:

• Building and implementing agentic AI solutions under guidance from Principal Engineers, including writing production code for MCP servers, RAG pipelines, and agent orchestration
• Supporting LoB teams with hands-on technical implementation, troubleshooting, and solution development
• Contributing to knowledge transfer and enablement activities by sharing technical knowledge and best practices with LoB engineering teams
• Collaborating with Principal Engineers on solution architecture and design decisions
• Participating in code reviews, technical documentation, and establishing best practices
• Supporting production deployments and post-deployment optimization activities
• Learning and applying Borealis platform capabilities to solve business challenges
• Contributing reusable components to shared platforms and repositories

You're our ideal candidate if you have:

• 5-8 years of software engineering experience with demonstrated expertise in building production systems
• 1-3 years hands-on experience with agentic AI systems, LLMs, and/or modern AI/ML frameworks
• Working knowledge of agentic AI patterns and design approaches (e.g., ReAct, Tool Use, agent orchestration)
• Proficiency in Large Language Models (LLMs), prompt engineering, and prompting techniques
• Experience building Retrieval Augmented Generation (RAG) systems, working with vector databases and embeddings
• Strong Python programming skills with ability to write clean, maintainable production code
• Familiarity with Model Context Protocol (MCP) or similar integration frameworks
• Experience with cloud platforms (AWS, Azure, or GCP) and modern DevOps practices
• Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines
• Understanding of security best practices, data governance, and compliance requirements
• Strong collaboration skills with ability to work effectively across technical and business teams
• Excellent communication skills for explaining technical concepts and sharing knowledge
• Ability to learn quickly in the rapidly evolving AI/ML landscape
• Comfort working in Agile environments with iterative delivery approaches

What's in it for you?

• Join a strategic team driving RBC’s enterprise AI transformation and competitive positioning
• Work on cutting-edge agentic AI technology with access to leading researchers, rich datasets, and significant computational resources
• Contribute to high-visibility, high-value business initiatives across the enterprise
• Leaders who support your development through mentoring and career growth opportunities
• Build deep expertise in agentic AI under guidance from experienced Principal Engineers
• Comprehensive Total Rewards Program including competitive compensation, bonuses, flexible benefits, and stock options where applicable

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, 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.

Job Skills

Agentic AI, AI Architecture, Applied Machine Learning, Applied Research, Artificial Intelligence (AI), Artificial Intelligence System (AIS), Critical Thinking, Cross-Functional Collaboration, Decision Making, Detail-Oriented, Large Language Models (LLMs), Product Development Design, Responsible AI, Stakeholder Management

Additional Job Details

Address: RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type: Salaried

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.