Agent Lead

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 role operates in a

high-ambiguity, rapid experimentation environment , identifying where agent-based approaches can unlock value-and equally, where they should not be applied.

You will define how

vendor agents (e.g., CRM-native), enterprise frameworks, and internally developed agents

coexist and interoperate within a governed ecosystem. This is not a pure engineering role-it is a

product-minded builder

who shapes, validates, and scales agentic patterns that can be reused across Wealth Management.

The mandate is to

move fast, prove value, and establish repeatable patterns , while aligning to enterprise architecture, risk, and AI governance standards.

What will you do?
Agentic Strategy & Use Case Qualification

Partner directly with Financial Advisors, field leadership, and business stakeholders ("side-of-desk") to identify high-value workflow opportunities

Evaluate when to apply

agentic AI vs. deterministic automation vs. no automation , with the authority to say "this is not an AI problem"

Define and prioritize

agentic use cases

aligned to advisor productivity, client engagement, and operational efficiency

Agent Design, Build & Rapid Experimentation

Lead

rapid POC development cycles

(fail fast / scale fast) for agentic workflows

Design multi-agent interactions across:

Vendor agents (e.g., CRM/Agentforce)

Enterprise agents (shared services / platforms)

Native/internal agents (event-driven, workflow-specific)

Establish reusable

agent design patterns

(prompting, orchestration, memory, tool usage, escalation paths)

Partner with AI Engineering to validate feasibility, performance, and scalability

Product Ownership & Lifecycle Accountability

Act as

Product Owner for agentic workflows -owning use case shaping through validated solution patterns

Ensure solutions are not "built and dropped" by:

Defining success metrics and adoption criteria

Driving iteration based on advisor feedback and usage telemetry

Maintain a

portfolio of agentic capabilities

with clear value articulation and reuse potential

Enterprise Alignment & Governance Integration

Engage with enterprise stakeholders (e.g.,

Borealis / enterprise AI, architecture, and platform teams ) to:

Align with approved agentic frameworks and standards

Leverage existing enterprise capabilities before building net new

Ensure all agentic solutions align to:

Model risk governance

Data privacy and security requirements

AI explainability and control frameworks

Agent Ecosystem & Standards Definition

Define how

agent ecosystems operate within RBC Wealth Management , including:

Interaction models between vendor, enterprise, and native agents

Guardrails for agent autonomy and decisioning

Cost-efficiency and performance considerations

Contribute to evolving

enterprise agent standards

through applied learnings

People Leadership & Capability Building

Manage and develop

Context Engineers / Prompt Engineers

Establish best practices in:

Context design and retrieval strategies

Prompt engineering and agent behavior tuning

Build a culture of

experimentation, accountability, and pragmatic problem solving

Field Engagement & Adoption

Travel (~25%) to branches and field locations to:

Observe advisor workflows firsthand

Identify friction points and real-world opportunities for agents

Validate usability and adoption of agentic solutions

What do you need to succeed?
Must-have

Proven experience building and deploying

agentic AI solutions

(multi-agent systems, orchestration frameworks, tool-using agents)

Strong understanding of

agent frameworks and architectures

(e.g., orchestration layers, memory models, tool integration, event-driven agents)

Demonstrated ability to operate as a

builder + product owner hybrid

Experience working across

business, engineering, and enterprise governance functions

Ability to rapidly prototype (POCs) and iterate based on real user feedback

Strong judgment in

when to use AI vs. when not to

Experience designing

workflow-driven automation

(not just models)

Leadership experience managing technical talent (e.g., prompt/context engineers)

Excellent stakeholder engagement skills-comfortable working "side-of-desk" with advisors and executives

Nice to have

Experience in

Wealth Management / Financial Services , particularly advisor workflows

Familiarity with CRM-based agent platforms (e.g., Salesforce Agentforce)

Exposure to

event-driven architectures

and real-time data integration

Understanding of

AI risk, model governance, and explainability frameworks

Experience integrating with enterprise AI platforms (e.g., internal AI platforms, cloud AI services)

Background in

human-centered design or workflow optimization

What's in it for you?

Direct ownership of one of the most

strategically important capabilities in RBC Wealth Management-agentic AI

Opportunity to define how

AI agents fundamentally reshape advisor productivity and client engagement

High visibility across business, technology, and executive leadership

Ability to operate in a

true "build, test, learn" environment

with real-world impact

Leadership of a

next-generation capability (context engineering + agent orchestration)

Influence on

enterprise-wide agent standards and architecture direction

Salary and Compensation
The good-faith expected salary range for the above position is $100,000 - $170,000 depending on factors including but not limited to the candidate's experience, skills, registration status; market conditions; and business needs. This salary range does not include other elements of total compensation, including a discretionary bonus and benefits such as a 401(k) program with company-matching contributions; health, dental, vision, life and disability insurance; and paid time-off plan.

Drives RBC's high performance culture

Enables collective achievement of our strategic goals

Generates sustainable shareholder returns and above market shareholder value

Job Skills
Agentic AI, Artificial Intelligence Technologies, Business Process Flows, Business Process Improvements, Commercial Acumen, Data Science, Decision Making, Enterprise Architecture (EA), Enterprise Architecture Framework, Generative AI, Generative AI Agents, Lean Business Processes, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)

Additional Job Details

Address: 250 NICOLLET MALL:MINNEAPOLIS

City: Minneapolis

Country: United States of America

Work hours/week: 40

Employment Type: Full time

Platform: WEALTH MANAGEMENT

Job Type: Regular

Pay Type: Salaried

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