VPII, Enterprise AI Portfolio Strategy Leader

LPL Financial•Charlotte, VA

10h•$178,293 - $297,155

About The Position

The VPII of Enterprise AI Strategy within LPL’s Transformation Office is responsible for shaping and driving the firm’s multi-year AI strategy and roadmap, with the goal of delivering AI-native products that transform advisor and employee experiences. The role partners closely with enterprise strategy and AI product and technology leaders to ensure the strategy informs product direction, prioritization, and funding decisions. The role also serves as Portfolio Lead for the enterprise AI portfolio, connecting business, product, technology, risk, and legal teams to translate strategic intent into measurable business outcomes. This is a business-seat leadership position that balances strategic judgment with execution and requires building alignment across the enterprise, resolving cross-functional tradeoffs, and maintaining a trusted view of portfolio status, risks, and dependencies. The position owns three related areas: AI strategy and business alignment; environmental scanning and competitive intelligence, including build-versus-buy, pricing and monetization, and AI deployment operating-model decisions; and enterprise AI portfolio leadership. Success involves keeping strategy current and actionable, surfacing market and execution signals early, involving risk and legal as design partners, and helping leaders make timely decisions that advance business outcomes.

Requirements

Demonstrated experience owning AI strategy from a business seat, including translating strategic direction into funding and prioritization decisions executed by product and technology organizations.
Track record of gaining alignment among business, product, technology, risk, and legal stakeholders who were not initially aligned, on timelines required by the business.
Fluency in AI commercial and competitive matters, including build-versus-buy tradeoffs, pricing and monetization models for AI-enabled products, and operating models for deploying AI at scale.
Experience using environmental scanning and competitive intelligence to inform decisions, with examples of decisions changed by findings.
Direct experience leading cross-functional, multi-stakeholder programs or initiatives and being accountable for outcomes across functional boundaries.
Ability to balance strategic agility with operational excellence and execute the operational details needed to deliver strategy.
Firsthand industry exposure to how AI is built, bought, priced, and deployed.
Ability to move quickly across multiple aspects of work without relying on sequential handoffs.
BA/BS degree required.

Nice To Haves

MBA or equivalent advanced degree.

Responsibilities

Partner with enterprise strategy and AI product and technology leaders to set the firm’s AI business strategy and determine strategic direction and sequencing.
Translate strategic direction into a roadmap that product and technology teams can execute against.
Connect AI strategy to prioritization, funding, and resourcing decisions.
Maintain and update the AI strategy on a defined cadence and adapt the roadmap to competitive, regulatory, or cost-related changes.
Own the firm’s outward-facing view of the AI industry and competitive landscape and turn findings into decisions.
Develop and align build-versus-buy positions, pricing and monetization approaches for AI-enabled offerings, and the AI deployment operating model.
Lead the enterprise AI portfolio across business, product, technology, risk, and legal stakeholders.
Surface execution risks and cross-functional blockers, resolve tradeoffs, and keep work focused on business outcomes.
Maintain a credible portfolio view of status, risks, and dependencies for leadership and cross-functional partners.
Track and report business outcomes, not only delivery milestones, on a cadence trusted by leadership.
Engage risk and legal partners early in roadmap design.
Build stakeholder alignment, make timely decisions when consensus is incomplete, and accelerate cross-enterprise execution.
Surface competitive shifts, regulatory direction, vendor and platform risks, and program execution risks early.