Agent Lead

RBC

Minneapolis (MN)

On-site

USD 100,000 - 170,000

Full time

27 hours ago

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Job summary

RBC Wealth Management in Minneapolis seeks an Agent Lead to transform Financial Advisor productivity through agentic AI workflows, bridging business problems with intelligent automation in a high-ambiguity environment.

You will own agentic use cases, design cross‑functional agent interactions (vendor, enterprise, and internal agents), and drive rapid experimentation while aligning with risk, governance, and enterprise standards.

Qualifications

Proven experience building and deploying agentic AI solutions (multi-agent systems, orchestration frameworks, tool-using agents).
Strong understanding of agent frameworks and architectures (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.

Responsibilities

Partner with Financial Advisors, field leadership, and stakeholders to identify high-value workflow opportunities.
Lead rapid POC development cycles for agentic workflows.
Design multi-agent interactions across vendor, enterprise, and native agents.
Define success metrics and adoption criteria; drive iteration based on feedback.
Maintain a portfolio of agentic capabilities with clear value and reuse potential.
Engage with enterprise stakeholders to align with standards.

Skills

Agentic AI

Multi-agent systems

Orchestration frameworks

Tool integration

Event-driven

Workflow automation

Product owner

Stakeholder management

Wealth management

CRM platforms

Python

Tools

Salesforce Agentforce

CRM platforms

Python

Job description

What is the opportunity?

The Agent Lead sits at the forefront of transforming Financial Advisor productivity through

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 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

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.

RBC’s compensation philosophy and principles recognize the importance of a highly qualified global workforce and plays a critical role in attracting, engaging and retaining talent that:

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

Employment Type

Full time

Platform

WEALTH MANAGEMENT