Lead Agentic AI Engineer

Royal Bank of Canada • Edina, MN

1d • $100,000 - $170,000 • Onsite

About The Position

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.

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 Haves

• 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

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

Benefits

• competitive compensation
• flexible benefits
• 401(k) program with company-matching contributions
• health, dental, vision, life, disability insurance
• paid-time off
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Opportunities to do challenging work
• Opportunities to build close relationships with clients

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed