Agent Lead

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.