Rbc
Financial Services
AIEngineerLead
Neural analysis suggests this role is
optimal for Lead candidates.
“AI Engineer Lead at Rbc. Skills: Generative AI, Deep Learning, Machine Learning, Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic frameworks. Design and build agentic frameworks that solve critical sales use cases. Develop conversational AI systems that assist sales professionals in client interactions”
What You'll Achieve.
Enhance client engagement, deal intelligence, and sales productivity across Capital Markets; Drive Generative AI initiatives that empower our Sales organization; Build and deploy AI solutions that give sales professionals real-time insights; Automate routine tasks; Enable sales professionals to focus on client relationships and closing deals; Ensure sales tools perform reliably at scale; Deliver better outcomes for clients and internal stakeholders; Make a lasting impact on how our Sales teams compete and win business at scale
Industry & Context.
Group Problem Solving
What They're Looking For.
Must Have
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, 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, Embrace of AI-first approach
Nice to Have
Kubernetes a plus
What You'll Do.
Design and build agentic frameworks that solve critical sales use cases
Develop conversational AI systems that assist sales professionals in client interactions
Embed Generative AI tools into Sales platforms
Architect end-to-end AI solutions covering experimentation
and production monitoring
Guide the team on best practices
Mentor team members on Generative AI implementation
Support Sales teams with cutting-edge AI-powered solutions
Enhance client engagement
and sales productivity across Capital Markets
Drive Generative AI initiatives that empower our Sales organization
Build and deploy AI solutions that give sales professionals real-time insights
Automate routine tasks
Enable sales professionals to focus on client relationships and closing deals
How You'll Work.
Team & Collaboration
Guide the team on best practices; Conduct code reviews; Mentor team members on Generative AI implementation; Work in a dynamic, collaborative, and high-performing team; Working together to deliver trusted advice; Effectively collaborate
Full Job Description
**_Job Description_** **AI Engineer, AidenSales** 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 **What will you do?** 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. **What do you need to succeed?** **Must-have** * 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 (RA
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