Lead Agentic AI Engineer
Royal Bank of Canada•Minneapolis, MN
•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
- 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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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
