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AI Discovery Specialist

Job in Cleveland, Cuyahoga County, Ohio, 44101, USA
Listing for: Sequoia Financial Group Llc
Full Time position
Listed on 2026-06-03
Job specializations:
  • IT/Tech
    AI Engineer, Data Analyst, Data Science Manager, Data Scientist
Salary/Wage Range or Industry Benchmark: 100000 - 130000 USD Yearly USD 100000.00 130000.00 YEAR
Job Description & How to Apply Below

AI Discovery Specialist

Professional Cleveland, OH, US

4 days ago Requisition

Sequoia Financial Group is a growing Registered Investment Advisor (RIA), headquartered in Northeast Ohio, offering financial planning and wealth management services. At Sequoia, we exist with a singular purpose: to enrich lives. Our values define how we behave and guide us through the pursuit of our purpose to enrich lives. At Sequoia, our core values are:

  • Integrity. We act in the best interests of others by providing an honest, consistent experience for our clients and team.
  • Passion
    . We pursue our full potential, seeking to continually enhance and evolve our ability to serve our clients and team.
  • Teamwork.We subordinate our egos to work together for the benefit of our clients.

Our promise to team members is that you will grow with us. From experienced advisors to new college grads to transitioning principals, every team member will find Sequoia a place to refine their professional mission, move into new opportunities, go deeper, and lead further. We are built to help you build a career here as a long-term contributor in our work to enrich lives for generations.

Summary

of the position

The AI Discovery Specialist is a strategic and hands-on role responsible for leading enterprise-wide AI discovery to identify, frame, and prioritize high-impact business problems that can be solved with AI, LLMs, and Data Science. This individual will analyze and optimize end-to-end business processes, build rapid proofs of concept, and drive automation initiatives that enhance personalization, operational efficiency, and strategic decision-making across Sequoia Financial Group.

This role sits at the intersection of AI/ML innovation, process optimization, rapid prototyping, and cross-department collaboration — ensuring that AI-first solutions are discovered, validated, and iterated to deliver clear, quantifiable value aligned with Sequoia's mission to redefine the client experience through data-driven insights and innovative technology.

Responsibilities
  • Lead enterprise-wide AI discovery to identify, frame, and prioritize high-impact business problems solvable with AI, LLMs, and Data Science, with clear, quantifiable value
  • Conduct user interviews, field observations, and journey walkthroughs to surface real problems behind stated requests; apply Jobs-To-Be-Done and behavioral insights
  • Create a Business Case Repository with ROI and Value Metrics to justify and rank use cases for AI-first Transformation
  • Convert qualitative insights into quantified problem definitions with baselines, success metrics, constraints, and value hypotheses
  • Build opportunity canvases and prioritization frameworks (impact, effort, risk, time-to-value) to focus on the most valuable use cases
  • Map current-state processes, identify pain points, and quantify improvement opportunities (cycle time, throughput, quality, cost)
  • Design future-state workflows considering AI/LLM augmentation, straight-through processing, and exception handling
  • Manage intake for new processes, automation requests, and optimization initiatives
  • Coordinate discovery workshops, kaizen events, and lessons-learned sessions with stakeholders
  • Design and build POCs using LLMs, retrieval-augmented generation (RAG), prompt engineering, RPA, and classical ML to validate feasibility quickly
  • Evolve POCs into MVPs with clear functional boundaries, guardrails, and success criteria; prepare handoffs for engineering or vendor buildout
  • Run short discovery sprints with user testing, A/B or champion–challenger evaluations, and weekly feedback loops
  • Maintain a transparent backlog and roadmap; time-box experiments and enforce clear "continue/pivot/stop" gates
  • Partner with leaders in Client Experience, Operations, Compliance, Planning, and Marketing to stand up shared automation and optimization initiatives
  • Align process definitions and business rules with the Data Dictionary and Data Governance artifacts to ensure consistency
  • Embed responsible-AI principles, data privacy, RBAC, and human-in-the-loop controls; escalate model/LLM limitations and biases with mitigations
  • Coordinate with Legal/Compliance on acceptable use, content controls,…
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