Rbc
financial services
SeniorDirectorAI,SolutionsPlatform
“Senior Director AI, Solutions Platform at Rbc. Skills: AI platform architecture, microservices, high-availability, developer platforms, MLOps, API design, governance. Build the enterprise-grade AI platform. own the infrastructure layer that every AI team builds on”
What You'll Achieve.
turns raw capability into production-ready solutions at scale; empowering business analysts; enabling developers to move at speed; evolve rapidly without accruing technical debt; supporting both real-time and batch AI workloads at enterprise scale; meeting production financial services uptime requirements; allowing business analysts to build and deploy AI workflows without engineering dependency; enable developers to integrate AI capabilities reliably; for production safety; ensuring all platform-deployed models meet enterprise risk standards; self-serve onboarding; deliver trusted advice to help our clients thrive and communities prosper; making a difference to our communities; achieving success that is mutual; making a difference and lasting impact; drive innovation; create value for our clients and communities
Industry & Context.
Decision Making
What They're Looking For.
Must Have
10+ years progressive experience in software engineering, platform architecture, or enterprise technology leadership, 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 developer experience orientation, command of authentication, authorization, and API security standards (OAuth 2.0, API gateway patterns, zero-trust principles)
Nice to Have
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
What You'll Do.
Build the enterprise-grade AI platform
own the infrastructure layer that every AI team builds on
design a platform accessible enough for non-technical users yet robust and governed enough for a regulated financial services environment
define the difference between AI that works in a lab and AI that delivers value in production at enterprise scale
Design a microservices-based platform architecture
Define data flow patterns
event streaming infrastructure
and asynchronous processing capabilities
Architect for high availability
Implement low-code/no-code application builder
Design and maintain comprehensive REST and gRPC APIs
Build model serving layer
Establish model governance workflows
Create and maintain a developer portal
How You'll Work.
Team & Collaboration
working together to deliver trusted advice; collaborative, progressive, and high-performing team; effectively collaborate
Communication Scope
trusted advice
Process & Methodology
technical debt
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