Lead Agentic AI Engineer

Royal Bank of Canada•Edina, MN

33d•$100,000 - $170,000

About The Position

The Agent Lead transforms Financial Advisor productivity through agentic AI workflows, connecting business problems with intelligent automation. This high-ambiguity, rapid-experimentation role defines how vendor, enterprise, and internally developed agents coexist and interoperate in a governed ecosystem. It is a product-minded builder role focused on shaping, validating, and scaling agentic patterns reusable across Wealth Management. The role partners with Financial Advisors, field leadership, business stakeholders, AI Engineering, and enterprise architecture and platform teams. It leads proof-of-concept development, owns agentic workflows from use-case definition through validation, establishes reusable agent design patterns, and manages Context Engineers/Prompt Engineers. Travel to branches and field locations is expected to observe workflows, validate usability, and encourage adoption. The position is a regular, salaried, full-time role in RBC Wealth Management, based at 250 Nicollet Mall in Minneapolis. It has a 40-hour work week and requires 25% travel. The expected salary range is $100,000–$170,000, depending on experience, skills, registration status, market conditions, and business needs. Eligible compensation may also include discretionary variable compensation.

Requirements

8–10 years of total engineering experience, including 2–3 or more years specifically building agentic or LLM systems beyond prototypes.
Hands-on experience with RAG architecture, including chunking tradeoffs, retrieval failures, and evaluation.
Experience building or extending tool integration layers that connect LLM agents to external systems.
Strong Python backend skills, including FastAPI, async, Pydantic, and streaming responses.
Proven experience building and deploying agentic AI solutions, including multi-agent systems, orchestration frameworks, and tool-using agents.
Strong understanding of agent frameworks, architectures, memory models, tool integration, and event-driven agents.
Ability to operate as a builder and Product Owner hybrid, with sound judgment about when to use AI and when not to.
Experience designing workflow-driven automation and working across business, engineering, and enterprise governance functions.
Leadership experience managing technical talent and strong 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 such as Salesforce Agentforce and with event-driven architectures.
Understanding of AI risk, model governance, explainability frameworks, and human-centered design.

Responsibilities

Partner with Financial Advisors, field leadership, and business stakeholders to identify high-value agentic workflow opportunities and assess whether AI or deterministic automation is appropriate.
Lead rapid proof-of-concept development cycles, designing multi-agent interactions involving vendor, enterprise, and native/internal agents.
Act as Product Owner for agentic workflows, shaping use cases, validating solution patterns, defining success metrics, and iterating based on advisor feedback and usage telemetry.
Establish reusable agent design patterns for prompting, orchestration, memory models, tool use, and escalation paths in collaboration with AI Engineering.
Align agentic solutions with approved frameworks, standards, and governance requirements by engaging enterprise stakeholders, architecture, and platform teams.
Manage and develop Context Engineers/Prompt Engineers and establish best practices in context design, retrieval strategies, and agent behavior tuning.
Travel to branches and field locations to observe advisor workflows, identify friction points, validate usability, and drive adoption of agentic solutions.