RBC
Lead Agentic AI Engineer, Wealth Management
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Job Description
What is the opportunity?
The Agent Lead sits at the forefront of transforming Financial Advisor productivity through agentic AI workflows—bridging business problems with intelligent automation. This is a high-ambiguity, rapid experimentation role where you'll define how vendor agents, enterprise frameworks, and internally developed agents coexist and interoperate within a governed ecosystem. This is not a pure engineering role—it's a product-minded builder role that shapes, validates, and scales agentic patterns reusable across Wealth Management.
What will you do?
- Partner directly with Financial Advisors, field leadership, and business stakeholders to identify high-value agentic workflow opportunities and evaluate when AI is the right solution vs. deterministic automation
- Lead rapid POC development cycles with authority to "fail fast / scale fast," designing multi-agent interactions across vendor agents (CRM/Agentforce), enterprise agents, and native/internal agents
- Act as Product Owner for agentic workflows—owning use case shaping through validated solution patterns, defining success metrics, and driving iteration based on advisor feedback and usage telemetry
- Establish reusable agent design patterns including prompting strategies, orchestration, memory models, tool usage, and escalation paths in collaboration with AI Engineering
- Engage with enterprise stakeholders (Borealis, architecture, and platform teams) to align with approved agentic frameworks, standards, and governance requirements
- Manage and develop Context Engineers/Prompt Engineers, establishing best practices in context design, retrieval strategies, and agent behavior tuning
- Travel (~25%) to branches and field locations to observe advisor workflows, identify friction points, validate usability, and drive adoption of agentic solutions
What do you need to succeed?
Must-have:
- Significant Software Engineering experience with proven experience of Agentic AI product incubation or agent development experience
- Masters in Computer Science, or equivalent experience
- Significant and extensive engineering experience—with proven experience specifically building agentic or LLM systems (not just prototypes)
- Hands-on RAG architecture—chunking tradeoffs, retrieval failures, evaluation
- Built or extended tool integration layers connecting LLM agents to external systems
- Strong Python backend—FastAPI, async, Pydantic, streaming responses
- Proven experience building and deploying agentic AI solutions (multi-agent systems, orchestration frameworks, tool-using agents)
- Strong understanding of agent frameworks, architectures, memory models, tool integration, and event-driven agents
- Demonstrated ability to operate as a builder + product owner hybrid with strong judgment on when to use AI vs. when not to
- Experience designing workflow-driven automation and working across business, engineering, and enterprise governance functions
- Leadership experience managing technical talent and excellent stakeholder engagement skills for "side-of-desk" collaboration
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Nice-to-have:
- Experience in Wealth Management, or Financial Services, particularly with advisor workflows
- Familiarity with CRM-based agent platforms (Salesforce Agentforce) and event-driven architectures
- Understanding of AI risk, model governance, explainability frameworks, and human-centered design
What is in it for you?
We thrive on the challenge to be our best - progressive thinking to keep growing and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
- A comprehensive Total Rewards Program including bonuses, flexible benefits, and competitive compensation
- Leaders who support your development through coaching and managing opportunities
- Opportunities to work with the best in the field
- Ability to make a difference and lasting impact
- Work in a dynamic, collaborative, progressive, and high-performing team
- A world-class training program in financial services.
Agency Notice
RBC Group does not accept agency résumés. Please do not forward résumés to our employees, nor any other company location. RBC Group only pay fees to agencies where they have entered into a prior agreement to do so and in any event do not pay fees related to unsolicited résumés. Please contact the Recruitment function for additional details.
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Job Skills
Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)
Additional Job Details
- Address: 100 BISHOPSGATE: LONDON
- City: London
- Country: United Kingdom
- Work hours/week: 35
- Employment Type: Full time
- Platform: WEALTH MANAGEMENT
- Job Type: Regular
- Pay Type: Salaried
- Posted Date: 2026-09-21
- Application Deadline: 2026-10-05
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
Our Employment Opportunities
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.
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