AI Engineer Lead

RBC•Toronto, ON

8d•Hybrid

About The Position

RBC Capital Markets is seeking an AI Engineer with deep expertise in Generative AI, neural networks, and transfer learning to support Sales teams with cutting-edge AI-powered solutions. You will lead the design and development of intelligent systems that enhance client engagement, deal intelligence, and sales productivity across Capital Markets. The Capital Markets Data AI and Research Technology (DART) team is looking for a hands-on AI Engineer to drive Generative AI initiatives that empower our Sales organization. You will build and deploy AI solutions that give sales professionals real-time insights, automate routine tasks, and enable them to focus on client relationships and closing deals. Hybrid Schedule: In-office 4 days per week

Requirements

A PhD or Master's degree in Computer Science, Machine Learning, Deep Learning, or equivalent hands-on experience.
Five or more years building Deep Learning or Machine Learning models in production environments.
Advanced proficiency in Python and hands-on experience with Generative AI frameworks and architectures.
Deep knowledge of retrieval-augmented generation (RAG), agentic frameworks, context and memory management, and tool/skills integration patterns.
Strong understanding of large language model architectures, inference, fine-tuning, and model deployment.
Experience with Anthropic models and Claude, including code generation capabilities.
In-depth knowledge of embeddings, re-rankers, and vector databases.
Expertise in ML experimentation, model evaluation, and monitoring in production.
Strong foundation in algorithms, data structures, and distributed computing.
Understanding of sales workflows, client intelligence use cases, or familiarity with how sales teams operate.
Embrace of AI-first approach: Actively incorporates AI tools and technologies into daily workflows to enhance productivity, streamline routine tasks, and drive efficiency. Demonstrates curiosity about emerging AI capabilities and applies them thoughtfully to deliver better outcomes for clients and internal stakeholders.

Nice To Haves

AI Agents
AI Frameworks
AI Systems
Application Integrations
Emerging Technologies
Enterprise Application Delivery
Group Problem Solving
Machine Learning (ML)
Python (Programming Language)
Responsible AI
Retrieval-Augmented Generation
Software Development Life Cycle (SDLC)
Solution Architecture

Responsibilities

Design and build agentic frameworks that solve critical sales use cases including client intelligence gathering, pitch content generation, deal summarization, and real-time conversation analysis.
Develop conversational AI systems that assist sales professionals in client interactions and help synthesize client intelligence across multiple data sources.
Embed Generative AI tools into Sales platforms, enabling seamless workflows for prospect research, proposal generation, and deal tracking.
Architect end-to-end AI solutions covering experimentation, model evaluation, and production monitoring to ensure sales tools perform reliably at scale.
Guide the team on best practices, conduct code reviews, and mentor team members on Generative AI implementation.

Benefits

bonuses
flexible benefits
competitive compensation
stock where applicable
Leaders who support your development through coaching and meaningful opportunities for growth.
The ability to make a lasting impact on how our Sales teams compete and win business at scale.
Work in a dynamic, collaborative, and high-performing team tackling some of the most challenging AI problems in financial services sales.
A world-class training program in financial services and AI best practices.
Flexible work/life balance options and progressive career opportunities across RBC.
Access to challenging work and the chance to build close relationships with Sales leadership and clients.