Lead Agentic AI Engineer

RBC Capital Markets, LLC; Minneapolis (MN); On-site; USD 100,000 - 170,000; Full time

Benefits offered by this job

401(k) with company matching

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

Paid time off

Job summary

RBC Capital Markets, LLC is seeking an Agent Lead to transform Financial Advisor productivity through agentic AI workflows. This product‑oriented builder role defines how vendor agents and internal agents interoperate within a governed ecosystem.

You will own use‑cases, set success metrics, and drive iteration based on advisor feedback and telemetry. Travel ~25% to observe workflows and drive adoption of new AI solutions.

Qualifications

• 8–10 years total engineering experience with 2–3+ years building agentic/LLM systems
• Hands-on RAG architecture including retrieval and evaluation
• Built or extended tool integration layers connecting LLM agents to external systems
• Strong Python backend skills (FastAPI, async, Pydantic, streaming)
• Proven experience building/deploying agentic AI solutions (multi-agent systems)
• Strong understanding of agent frameworks, memory models, tool integration and event-driven agents
• Builder + product owner hybrid with judgment on AI vs non-AI solutions
• Experience designing workflow-driven automation across business, engineering and governance
• Leadership in managing technical talent and stakeholder engagement

Responsibilities

• Partner with Financial Advisors and stakeholders to identify high-value agentic opportunities
• Lead rapid POC cycles and design multi-agent interactions
• Act as Product Owner for agentic workflows and define success metrics
• Establish reusable agent design patterns including prompting, orchestration and memory
• Collaborate with AI Engineering on context design and retrieval strategies
• Engage with enterprise teams to align with governance and frameworks
• Develop Context/Prompt Engineers and promote best practices
• Travel ~25% to observe workflows and drive adoption

Skills

Engineering experience

Agentic/LLM systems

RAG architecture

Tool integration

Python backend

FastAPI/async

Product owner

Leadership

Workflow automation

Stakeholder engagement

Tools

Salesforce Agentforce

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 high‑ambiguity, rapid‑experimentation role defines how vendor agents, enterprise frameworks, and internally developed agents coexist and interoperate within a governed ecosystem. It is a product‑oriented builder role that shapes, validates, and scales agentic patterns reusable across Wealth Management.

What will you do?

• 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 versus 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.

What do you need to succeed?

Must‑have

• 8‑10 years total engineering experience, with 2‑3+ years specifically building agentic or LLM systems (not just prototypes).
• Hands‑on RAG architecture—chunking trade‑offs, retrieval failures, evaluation.
• Built or extended tool integration layers connecting LLM agents to external systems.
• Strong Python backend skills—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 versus non‑AI solutions.
• 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.

What's in it for you?

• A comprehensive total‑rewards program including competitive compensation and flexible benefits such as a 401(k) with company matching, health, dental, vision, life, disability insurance, and paid‑time off.
• Leadership support through coaching and management opportunities.
• Opportunity to make a lasting impact and build close relationships with clients.
• Work in a dynamic, collaborative, progressive, and high‑performing team.
• Chance to take on challenging work and pursue professional growth.

Salary

Expected salary range: $100,000–$170,000, depending on experience, skills, and market conditions.

Location

Minneapolis, United States.