Senior Manager AI Engineering - RBC, Vancouver

About this opportunity

The Senior Manager, AI Engineering (AML & Fraud) will lead a team delivering engineering solutions for fraud and AML capabilities across global groups. The role combines hands-on technical work with people leadership and stakeholder relationship management. This role plays a pivotal part in reshaping the future of US Corporate Functions through cutting-edge technology. In this role you will lead a team of engineers, setting technical direction and ensuring successful delivery of scalable, production ready solutions. You will champion the adoption of AI, machine learning, and emerging technologies, while driving the integration of CNB US Functions technology in Fraud and AML with RBC Enterprise offerings and taking ownership of the applications you deliver.

You will build strong relationships with business and technology leaders across the organization, manage stakeholder expectations, and prepare executive updates. Your strong foundation in software development and cloud systems will allow you to stay hands-on and step in wherever delivery needs it most.

Your impact

• Pioneer End-to-End solutions from prototyping to deployment, owning the full lifecycle of AI initiatives including architecture changes and committed timelines for core Fraud and AML CNB Functions technology areas
• Take technical ownership of Fraud and AML applications, including Application Control Assessments, data attestations, security vulnerability remediation, and operational hygiene
• Lead, mentor, and grow a team of engineers and contractors, setting technical direction and quality standards
• Support the team through integration testing, development, and architecture analysis, staying hands-on to unblock delivery and guide the team toward sound engineering decisions
• Lead the integration of CNB US Functions applications into RBC Common Platform, working with business stakeholders and Target Tech teams to ensure smooth adoption
• Gather requirements and translate business objectives into actionable technical strategies, in partnership with business and technology leaders
• Drive solution architecture and engineering design decisions for integration and platform needs, with a focus on performance, security, and compliance
• Build and deploy cloud-native solutions on AWS, Azure, or GCP, using Kubernetes and Docker to ensure scalability and reliability
• Maintain a working understanding of enterprise operations, including shared services, Splunk, Elastic, and performance monitoring, to support application health and incident response
• Address ethical AI, data governance, and regulatory considerations in financial services
• Prepare executive updates and manage stakeholder expectations across global teams
• Create and contribute to AI first mindset within team by coaching and mentoring colleagues
• Build and sustain strong relationships with stakeholders across global teams, translating complex technical information into clear, non-technical terms to support informed decision-making

Requirements

Must have qualifications include:

• 7+ years of experience leading an engineering team, with a hands-on approach that stays close to the code and steps in to unblock delivery when needed
• Must have a strong technical background, with practical experience supporting integration testing, and development with one or more language (.Net, Java, Python)
• Proven track record of leading the design, build, and deployment of cloud-native solutions on AWS, Azure, or GCP, using Kubernetes and Docker, and guiding teams to scalable, reliable outcomes
• Experience leading teams that scale and deploy cloud-based applications, reduce latency, and monitor performance, owning solutions from development through to production
• Experience guiding teams on API design, function calling integration, and data orchestration, with a solid grounding in ML fundamentals to inform sound engineering and delivery decisions
• Experience supporting applications after go-live, including incident response and working knowledge of enterprise operations, such as Splunk, Elastic, and performance monitoring
• Experience making solution architecture and design decisions with a focus on performance, security, and compliance
• Strong relationship-building skills, with the ability to translate technical information into clear, non-technical terms and prepare executive updates
• Well versed in Agile and Kanban methodologies, with a proven record of driving technical delivery, managing sprint or flow-based planning, and keeping work predictable and on schedule
• Understanding of data governance, ethical AI, and regulatory considerations

Nice to have qualifications include:

• Exposure to fraud or AML domains, with an understanding of core concepts and banking terminology
• Experience operating within a regulated environment, with an understanding of compliance requirements and their impact on engineering delivery
• Experience with Large Language Models (LLMs), transformer-based architecture, and prompt engineering techniques
• Hands-on experience with Retrieval-Augmented Generation (RAG) systems and vector databases for knowledge retrieval
• Knowledge or experience in prompt engineering and AI based SDLC (Claude, GitHub Copilot)
• Familiarity with Python and AI frameworks (LangChain, AutoGen, CrewAI)
• Familiarity with AI decision-making frameworks and multi-agent problem-solving strategies, including experience with agent architecture design

Compensation and perks

• 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
• Opportunities to do challenging work