# Agent Lead

**Company**: RBC
**Location**: Minneapolis, Minnesota
**Experience**: senior
**Job type**: full-time
**Salary**: $100,000 - $170,000
**Category**: Engineering
**Industry**: Finance

**Apply**: https://rbc.wd3.myworkdayjobs.com/en-US/RBCGLOBAL1/job/Minneapolis-Minnesota-United-States-of-America/Lead-Agentic-AI-Engineer_R-0000182936-2?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/agent-lead-afbb7a17-b62/

## Description

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.

**Responsibilities**

- 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

**Requirements**

- 8–10 years total engineering experience , with 2–3+ years 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

**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

**Benefits**

- A comprehensive Total Rewards Program include competitive compensation and flexible benefits, such as 401(k) program with company-matching contributions, health, dental, vision, life, disability insurance, and paid-time off.

- Leaders who support your development through coaching and managing opportunities.

- Ability to make a difference and lasting impact.

- Work in a dynamic, collaborative, progressive, and high-performing team.

- Opportunities to do challenging work.

- Opportunities to build close relationships with clients.

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## Skills

### Required
- Python
- Machine Learning (ML)
- Natural Language Processing (NLP)
- Predictive Analytics
- Data Science
- Decision Making

### Nice to have
- Experience in Wealth Management or Financial Services
- Familiarity with CRM-based agent platforms (Salesforce Agentforce)
- Understanding of AI risk, model governance, explainability frameworks, and human-centered design

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Source: [Apply at rbc.wd3.myworkdayjobs.com](https://rbc.wd3.myworkdayjobs.com/en-US/RBCGLOBAL1/job/Minneapolis-Minnesota-United-States-of-America/Lead-Agentic-AI-Engineer_R-0000182936-2?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)