Head of Applied AI, Digital and Global Investments

Royal Bank of CanadaToronto, ON
Onsite

About The Position

Wealth Management Data & AI is responsible for delivering a global data foundation and innovative AI capabilities across all of Wealth Management’s global businesses. We are building a high-impact technical team that will deliver cutting-edge AI solutions – underpinned by a state-of-the-art data foundation – for our Digital and Global Investment teams. In this role, you will have unique access to rich and massive datasets, computational resources, and tooling necessary to build game-changing AI/ML models and GenAI solutions. This is a rare opportunity to help shape the future of our business and power innovative offerings fit for the next generation of Wealth Management clients. We are looking for an exceptional Head of Applied AI to serve as the technical leader of this team. This is a role for someone who thrives at the intersection of hands-on technical depth, people leadership, and strategic vision – someone who can conceptualize, architect, and deliver high-impact AI solutions while also building, mentoring, and scaling a team of talented data scientists and ML engineers. You will set the technical direction, drive prioritization with a business-first mindset, and foster a culture that combines rigorous, first-principles problem solving with a results-oriented delivery mindset.

Requirements

  • Master’s degree (or higher) in computer science, statistics, machine learning, applied mathematics, or a related quantitative field
  • 8-10+ years of progressive experience in AI/ML/data science, with a strong track record of independently delivering high-impact solutions in production environments
  • 3+ years of experience leading technical teams, including providing technical direction, managing workload, mentoring, and developing talent
  • Deep, hands-on expertise across the AI/ML lifecycle: problem abstraction, data engineering, feature development, model training and evaluation, and deployment
  • Experience leading the design and architecture of an AI stack (e.g., data management and infrastructure, model training, MLOps, etc.) on a cloud-based platform (e.g., AWS, Azure, Snowflake, Databricks)
  • Strong foundation in both traditional ML techniques (supervised/unsupervised learning, time series, optimization) and modern GenAI approaches (LLMs, RAG, agentic AI, prompt engineering)
  • Experience building PoCs and prototypes to demonstrate novel concepts and solutions in practical application contexts
  • A passion for problem solving and proven ability to think from first principles – decomposing ambiguous business problems into structured, solvable technical challenges
  • Pragmatic delivery mindset – comfort optimizing for progress over perfection, building within existing tooling and framework, and taking an iterative approach to the target end-state/vision
  • Excellent communication skills with the ability to translate complex technical work into compelling narratives for business stakeholders
  • Proficiency in Python and the modern ML/AI stack (e.g., PyTorch, TensorFlow, Hugging Face, LangChain, cloud ML platforms)

Nice To Haves

  • PhD in a relevant quantitative or AI/ML discipline
  • Experience in wealth management, investment management, or financial services more broadly
  • Track record of publishing applied research or contributing to the broader AI/ML community
  • Experience working in a matrixed, global organization and partnering across regions

Responsibilities

  • Own the technical vision and architecture for AI solutions supporting our Digital and Global Investment teams, ensuring they are robust, scalable, and production-ready
  • Lead the design and delivery of AI/ML and GenAI solutions across the full development lifecycle – from problem framing and data exploration through model development, validation, and deployment
  • Provide hands-on technical guidance to the team, helping them navigate complex modeling challenges, debug difficult problems, and make sound architectural decisions
  • Stay current with emerging AI technologies – including LLMs, generative and agentic AI, and novel ML methodologies – and determine how and when to incorporate them into the team’s work
  • Lead, mentor, and develop a team of 5-10 AI scientists and ML engineers at varying levels of seniority
  • Foster a high-performance team culture grounded in intellectual curiosity, collaboration, and accountability
  • Provide regular coaching and career development support, helping team members grow their technical skills and business acumen
  • Manage team workload and priorities, ensuring the right balance between delivery commitments and innovation or exploration work
  • Work closely with business stakeholders to deeply understand their business problems and pain points, translate them into well-defined technical problems, prioritize the highest-impact opportunities, and build a strategic roadmap of AI solutions
  • Act as the bridge between business strategy and technical execution, ensuring the team’s work is aligned with top strategic priorities and delivers tangible business value
  • Communicate complex AI concepts and solution trade-offs clearly to both technical and senior non-technical audiences, building trust and credibility across the organization
  • Contribute to the broader Data & AI strategy and roadmap, bringing a practitioner’s perspective to strategic planning

Benefits

  • 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
  • Flexible work/life balance options
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