RBC Capital Markets
Financial Services
AIEngineer
“AI Engineer at RBC Capital Markets. Skills: Generative AI, Deep Learning, Machine Learning, Python, retrieval-augmented generation (RAG), agentic frameworks, large language model architectures, model deployment. 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”
Industry & Context.
Group Problem Solving; tackling some of the most challenging AI problems in financial services sales
What They're Looking For.
Must Have
PhD or Master's degree in Computer Science, Machine Learning, Deep Learning, or equivalent hands-on experience, 2-5 years building Deep Learning or Machine Learning models in production environments, Advanced proficiency in Python, Hands-on experience with Generative AI frameworks and architectures, Deep knowledge of retrieval-augmented generation (RAG), Deep knowledge of agentic frameworks, Deep knowledge of context and memory management, Deep knowledge of tool/skills integration patterns, Understanding of large language model architectures, Understanding of large language model inference, Understanding of large language model fine-tuning, Understanding of large language model deployment, Experience with Anthropic models and Claude, Experience with code generation capabilities, In-depth knowledge of embeddings, In-depth knowledge of re-rankers, In-depth knowledge of vector databases, Expertise in ML experimentation, Expertise in model evaluation, Expertise in monitoring in production, Foundation in algorithms, Foundation in data structures, Foundation in distributed computing, Understanding of sales workflows, Understanding of client intelligence use cases, Familiarity with how sales teams operate, Embraces an AI-first approach
Nice to Have
AI Agents, AI Concepts, AI Frameworks, Application Integrations, Enterprise Application Delivery, Group Problem Solving, Machine Learning (ML), Retrieval-Augmented Generation, Software Development Life Cycle (SDLC)
What You'll Do.
Design and build agentic frameworks that solve critical sales use cases including client intelligence gathering
pitch content generation
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
Architect end-to-end AI solutions covering experimentation
and production monitoring to ensure sales tools perform reliably at scale
Guide the team on best practices
Mentor team members on Generative AI implementation
How You'll Work.
Team & Collaboration
working together; collaborative; Group Problem Solving; effectively collaborate; Collaboration; working together as One RBC
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