Sr. Director, AI Leader & Discovery Specialist

Sequoia Financial Group

$150K — $180K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years in technology leadership, product delivery, or business development
  • 5+ years in AI, data, or a related technology role with practical experience in AI solution architecture
  • Ability to identify transformation opportunities and translate them into technical projects
  • Experience leading cross-functional teams in dynamic environments
  • Strong business acumen with proficiency in finance and executive communication
  • Experience in regulated industries like financial services or healthcare
  • Hands-on knowledge of modern AI frameworks and methodologies.

Responsibilities

  • Lead the Applied AI Team while setting technical and operational standards
  • Develop and communicate a decision tree for sizing AI opportunities
  • Manage the delivery pipeline and prioritize new projects based on capacity
  • Design and enforce adoption mechanisms for AI solutions in workflows
  • Coach team leads and conduct performance reviews to foster development
  • Engage with primary stakeholders and align initiatives with strategic KPIs
  • Own the AI delivery model and maintain governance documents.

Benefits

  • Opportunity to lead a team and influence company-wide AI strategy
  • Engagement in a fast-paced environment with transformational initiatives
  • Access to professional development resources and training
  • Position with high visibility to senior leadership and executive stakeholders
  • Involvement in the governance and evolution of AI frameworks.
Full Job Description
Position Summary:

The Applied AI Leader and AI Discovery Specialist serves as the operational leader of the Applied AI Team and the organization's AI Discovery function, filling a dual-role player-coach. This position currently leads a team of five: the AI Solutions Lead, AI Delivery Manager, Agentic AI Delivery Manager, Agentic Transition Lead, and Agentic Discovery Lead. This role reports directly to the Head of AI and Data and is accountable for the health of the delivery pipeline, team development, and continuous scouting for transformation opportunities across Sequoia.

Direct Manager: Head of AI and Data.

Operating Committee oversight and quarterly reviews.

Monthly strategic alignment with CTO and Head of AI and Data.

Primary business stakeholder engagement: Operating Committee (OC) members and their direct reports.

Key Responsibilities:

Applied AI Team Operations

Lead the Applied AI Team as a whole. Set technical and operational standards. Conduct regular team meetings. Hire, onboard, and develop the team. Remove blockers and escalate decisions. Maintain team morale.

AI Opportunity Discovery

Own and communicate the decision tree that sizes opportunities (small/medium/large/XL) and determines approval authority. Monitor active work across the organization to identify when peer-to-peer AI usage (skills, agents, tools) crosses the institutionalization threshold and requires formal governance review.

Pipeline Management

Maintain the active pipeline at various stages. Prioritize new opportunities against available capacity. Make go/no-go decisions. Communicate pipeline status to the Head of AI and Data quarterly.

Adoption Architecture

Design and enforce adoption mechanisms that embed AI solutions into mandatory workflows (not optional overlays). Co-own adoption KPIs with business unit leaders; clarify behavioral accountability and workflow enforcement before deployment. Escalate to OC if structural adoption barriers emerge during MVP or Product phase.

Team Coaching

Coach the AI Delivery Manager and AI Solutions Lead on business communication and escalation. Mentor Agentic team leaders. Conduct quarterly performance reviews. Identify development and external training opportunities.

Stakeholder and Executive Engagement

"Primary stakeholder engagement: Operating Committee (OC) members and their direct reports (business unit leaders, function heads). Conduct quarterly discovery review meetings with each OC leader to align AI initiatives with their strategic KPIs. Secondary engagement: Management Committee (MC) for strategic alignment and resource decisions

Governance and Evolution

Own the definition of the AI delivery model. Document role accountabilities and phase gates. Maintain the responsibility matrix. Ensure governance stays lightweight, not bureaucratic.

Required Experience:
  • 10+ years in technology leadership, product delivery, or business development
  • 5+ years in AI, data, or adjacent technology roles with hands-on understanding of AI solution architecture and delivery complexity
  • Proven ability to identify business transformation opportunities and translate them into technical initiatives
  • Track record leading cross-functional teams (5-10 people) in fast-moving, ambiguous environments
  • Strong business acumen and ability to speak the language of finance, operations, and executive leadership
  • Experience working in regulated industries (financial services, healthcare, compliance-heavy domains)
  • Hands-on understanding of modern AI frameworks and methodologies (Claude, foundation models, prompt engineering, agentic workflows)
  • Ability to operate as a player-coach, balancing team leadership with individual contributor work

Preferred Experience:
  • Background in wealth management, financial advisory, or banking
  • Prior experience with AI adoption, change management, and user adoption strategies
  • Familiarity with Salesforce and financial advisory systems (Orion, Black Diamond, Addepar; eMoney, MoneyGuide)
  • Track record in identifying and scaling high-impact initiatives from conception to scale
  • Executive presence and comfort when presenting to boards or senior leadership

Core Competencies:

Strategic Vision: Sees opportunities others miss. Frames problems as AI transformation opportunities. Articulates a 2 to 3-year strategy that executives believe in.

Operational Excellence: Runs a tight ship. Maintains clear accountability, decision velocity, and delivery discipline. Ships iteratively.

Stakeholder Leadership: Builds confidence with executives and business stakeholders. Communicates complex concepts in business language. Negotiates effectively.

Team Development: Hires strong people and develops them into leaders. Creates psychological safety for risk-taking. Provides coaching that people experience as helpful.

Technical Credibility: Understands AI solution architecture and delivery complexity. Makes credible technical decisions. Defers to experts while asking hard questions.

Adoption Obsession: Designs delivery and success metrics around adoption, treating it as the primary constraint. Measures success by behavior change, not feature delivery.

Discovery Rigor: Qualifies opportunities before they consume delivery capacity. Asks hard discovery questions: Who owns the adoption outcome? What behavioral change is required? What is the cost of inaction? Builds scaffolded business cases that de-risk investment decisions. Says no when the business sponsor commitment is insufficient, or the adoption architecture is unclear.

Working Conditions:

Frequent minimal physical effort such as sitting, prolonged periods working on a computer, standing and walking is required for this role. Depending on location, occasional moving and lifting light equipment and/or furniture may be required. This role may require occasional travel, including travel to client sites, company offices, or industry events, as needed.

Employer Rights:

This job description does not list all of the job duties of the job. You may be asked by your supervisors or managers to perform other duties. You may be evaluated in part based upon your performance of the tasks listed in this job description. The employer has the right to revise this job description at any time. This job description is not a contract for employment and either you or the employer may terminate your employment at any time for any reason.

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