AI Engineer

Job Description

WHAT IS THE OPPORTUNITY?

Be the organization's foremost practitioner and technical authority on AI platform engineering. As Principal AI Engineer, you'll own foundational architecture decisions that will underpin enterprise AI for years to come, design systems that enable teams across the organization to move at speed and solve the most complex technical challenges at the intersection of AI, infrastructure, and security. This role combines architectural vision with hands-on engineering depth by defining reference architectures, establishing technical standards, and building the API platforms and infrastructure that scale AI beyond proof-of-concept into production at enterprise scale.

WHAT WILL YOU DO?

• Serve as the enterprise's foremost technical authority on AI platform architecture, owning foundational decisions on infrastructure design, component composition, and platform evolution

• Define and maintain reference architectures covering API gateway design, LLM access patterns, model serving infrastructure, and integration frameworks

• Design, build, and own the enterprise AI API layer including internal APIs and SDKs providing standardized, secure access to AI capabilities across the organization

• Establish API design standards, versioning policies, and deprecation protocols ensuring the platform's interfaces are reliable, developer-friendly, and maintainable

• Architect integration of external AI services, including Anthropic Claude API and other LLM providers, ensuring connectivity is secure, governed, and operationally robust

• Design API gateway and rate-limiting framework for LLM access, balancing cost controls, fairness, and service reliability under variable load

• Set and uphold technical standards for AI platform engineering by establishing coding standards, design principles, testing requirements, and documentation expectations

• Develop technical guides, engineering playbooks, and reference implementations that give development teams a clear starting point for common AI patterns

WHAT DO YOU NEED TO SUCCEED?

Must have:

• 10+ years software or platform engineering experience, with at least 5 years focused on AI/ML infrastructure, API platform engineering, or large-scale distributed systems

• Demonstrated track record designing and delivering enterprise-grade AI platforms with direct, hands-on engineering contribution at the most complex levels

• Deep expertise in LLM API integration and production deployment (Anthropic Claude, OpenAI, Azure OpenAI, or equivalent at enterprise scale)

• Strong proficiency in API design and gateway engineering including RESTful patterns, authentication/authorization frameworks (OAuth2, JWT), rate limiting, and observability

• Hands-on experience with vector databases and RAG pipeline architecture (Pinecone, Weaviate, pgvector, Chroma, or equivalent)

Nice-to-have:

• Experience operating in regulated industries (financial services, healthcare) with familiarity of compliance and security constraints for AI infrastructure

• Hands-on experience implementing AI security controls including prompt injection mitigation, output filtering, and PII detection

• Familiarity with AI governance frameworks and responsible AI engineering practices including model audit logging and fairness monitoring

• Experience with MLOps platforms and model serving infrastructure (Azure ML, AWS SageMaker, Databricks, MLflow, BentoML, or equivalent)

• Contributions to open-source AI/platform engineering projects or technical publications at recognized forums

What's in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable

• Leaders who support your development through coaching and managing opportunities

• Ability to make a difference and lasting impact

• Work in a dynamic, collaborative, progressive, and high-performing team

• A world-class training program in financial services

• Flexible work/life balance options

• Opportunities to do challenging work

#LI-POST

#TechPJ

Job Skills

Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages

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

Posted Date:

2026-04-03

Application Deadline:

2026-04-30

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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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.