Senior Director AI, Solutions Platform

RBC•Toronto, ON

2d•Onsite

About The Position

Build the enterprise-grade AI platform that turns raw capability into production-ready solutions at scale. As Senior Director, you'll own the infrastructure layer that every AI team builds on—from low-code/no-code interfaces empowering business analysts to production APIs enabling developers to move at speed. Reporting to the Vice President AI, Architecture, Tools & Innovation, you'll design a platform accessible enough for non-technical users yet robust and governed enough for a regulated financial services environment. This role defines the difference between AI that works in a lab and AI that delivers value in production at enterprise scale.

Requirements

10+ years progressive experience in software engineering, platform architecture, or enterprise technology leadership, with at least 4 years in senior capacity
Demonstrated experience designing and operating high-availability, enterprise-grade platforms with microservices architecture and production-scale reliability
Deep technical fluency in modern AI/ML infrastructure including model serving, MLOps, containerization, and cloud-native deployment patterns
Hands-on experience building developer platforms, internal tooling, or API ecosystems with multi-language SDK support and strong developer experience orientation
Strong command of authentication, authorization, and API security standards (OAuth 2.0, API gateway patterns, zero-trust principles)

Nice To Haves

Experience operating in financial services or similarly regulated enterprise environment with compliance, audit, and risk governance requirements
Familiarity with low-code/no-code platform design and UX challenges of serving both technical and non-technical users
Exposure to event streaming technologies (Kafka, Kinesis), data drift detection, and real-time model observability tooling
Experience with multi-region cloud architecture, platform SRE practices, and operational disciplines for enterprise-grade availability
Familiarity with LLM deployment patterns, vector databases, and infrastructure for generative AI applications at scale

Responsibilities

Design a microservices-based platform architecture with clear API contracts, defined service boundaries, and modularity to evolve rapidly without accruing technical debt
Define data flow patterns, event streaming infrastructure, and asynchronous processing capabilities supporting both real-time and batch AI workloads at enterprise scale
Architect for high availability with multi-region failover, intelligent load balancing, and resilience patterns meeting production financial services uptime requirements
Implement low-code/no-code application builder with form-based configuration interfaces allowing business analysts to build and deploy AI workflows without engineering dependency
Design and maintain comprehensive REST and gRPC APIs with Python, Java, Go, and Node.js SDKs that enable developers to integrate AI capabilities reliably
Build model serving layer supporting multiple model types and frameworks, with versioning, canary deployment, and model monitoring for production safety
Establish model governance workflows including approval gates, audit logging, and compliance checkpoints ensuring all platform-deployed models meet enterprise risk standards
Create and maintain a developer portal with self-serve onboarding, interactive documentation, sandbox environments, and support pathways

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