Staff AI Engineer

Royal Bank of Canada•Toronto, ON

4d•Onsite

About The Position

Be the organization's foremost practitioner and technical authority on AI platform engineering. As an AI Engineer, you'll 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. In this role, you will work hands-on to build the API platforms and infrastructure that scale AI beyond proof-of-concept into production at enterprise scale.

Requirements

8+ 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 Haves

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

Responsibilities

Create AI platform architecture, owning infrastructure design, component composition, and platform evolution
API gateway design, LLM access patterns, model serving infrastructure, and integration frameworks
Build, and own the enterprise AI API layer including internal APIs and SDKs providing standardized, secure access to AI capabilities across the organization
Build on the established API design standards, versioning policies, and deprecation protocols ensuring the platform's interfaces are reliable, developer-friendly, and maintainable
Create 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

Benefits

bonuses
flexible benefits
competitive compensation
commissions
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