SVP, Head of Enterprise AI Program Management

Jefferies•New York, NY

1d•$225,000 - $300,000•Onsite

About The Position

The Head of Enterprise AI Program Management will provide the program management discipline required to turn Jefferies’ Enterprise AI strategy into an executable, measurable firmwide delivery program. The role will coordinate and govern delivery across the AI workstreams, ensuring scope, ownership, milestones, dependencies, risks, and outcomes are clearly defined and actively managed. This position requires strong project and program management capability, executive presence, financial and commercial judgment, and the ability to create structure, momentum, and accountability across a complex, matrixed AI transformation program.

Requirements

Significant experience supporting or managing large-scale technology, AI, digital transformation, or strategic programs within financial services or another complex, regulated environment.
Proven ability to bring structure to complex or evolving programs through integrated project plans, governance routines, RAID management, stakeholder forums, milestone tracking, and executive reporting.
Strong understanding of program delivery, portfolio management, business-case development, prioritization, financial governance, benefits realization, risk management, and organizational change.
Demonstrated ability to influence senior business, technology, finance, and control-function leaders without relying on direct authority.
Exceptional written, verbal, financial, commercial, and executive communication skills, including the ability to create concise decision-ready materials.

Nice To Haves

Experience managing AI, automation, digital transformation, data, platform, infrastructure, or innovation delivery programs within investment banking, capital markets, or broader financial services.
Familiarity with enterprise AI operating models, responsible AI, model and data controls, FinOps, consumption-based technology economics, and regulated technology environments.
Working familiarity with AI delivery concepts such as use-case lifecycle management, model/data dependencies, production readiness, responsible AI controls, evaluation, adoption tracking, and post-implementation monitoring.
Experience with scaled product delivery, cross-functional pods, use-case lifecycle governance, and transition from pilot to production.

Responsibilities

Establish and operate the Enterprise AI PMO, including program governance, reporting cadence, delivery standards, dependency tracking, escalation paths, and decision forums.
Translate the multi-year AI strategy into an integrated program plan with workstreams, accountable owners, milestones, dependencies, required inputs, and measurable outcomes.
Maintain a single enterprise view of roadmap progress, risks, issues, actions, decisions, dependencies, resource constraints, and executive follow-ups across the AI program.
Manage the AI use-case intake process and ensure proposals are captured consistently with business objective, sponsor, expected value, feasibility, delivery approach, control considerations, and required funding.
Coordinate prioritization discussions so leadership can evaluate use cases against strategic value, readiness, complexity, cost, delivery capacity, risk, and expected adoption.
Partner with business transformation leads and workstream owners to convert approved use cases into clear project plans, milestones, acceptance criteria, and success metrics.
Support milestone-based funding governance across approval, proof-of-value, scale-up, and transition to business-as-usual, in partnership with Finance and accountable initiative owners.
Partner with the CFO organization and Controllers to validate assumptions, baselines, savings, realized outcomes, and ongoing investment performance.
Produce portfolio-level views of investment, forecast, value at risk, realized benefits, adoption, and expected returns for senior leadership.
Coordinate delivery across cross-functional AI workstreams and pods by aligning accountable technical, business, and control-function owners around shared plans, milestones, and outcomes.
Maintain integrated project plans, timelines, milestone trackers, RAID logs, dependency maps, action registers, and escalation items across the Enterprise AI Program.
Facilitate structured delivery cadences, identify blockers early, drive follow-ups to resolution, and help ensure workstream owners have the inputs and decisions needed to maintain execution momentum.
Track program-level budget, forecast, resource assumptions, funding approvals, and financial reporting inputs for the Enterprise AI Program in partnership with Technology Finance and workstream owners.
Partner with FinOps and Technology Finance to establish transparency over compute, token consumption, infrastructure, licenses, vendor, and consulting costs.
Provide clear views of committed spend, utilization, run rate, forecast variance, cost risks, and linkage to approved use cases and business outcomes.
Coordinate with security, data governance, privacy, legal, compliance, model risk, architecture, and audit partners to embed required controls into the program lifecycle.
Help ensure initiatives progress through defined control gates with appropriate documentation, approvals, evidence, and traceability.
Maintain program-level risk reporting and support timely escalation of material control issues, decisions, and remediation actions through the appropriate forums.
Prepare concise, decision-oriented status reporting for the CIO, CFO, Enterprise AI leadership, steering forums, QBRs, and other senior governance venues.
Facilitate working sessions and leadership forums, capture decisions, document actions, confirm owners, track deadlines, and support timely escalation where needed.
Act as a central coordination point for program status, priorities, risks, dependencies, escalations, and accountability across business, technology, and corporate functions.
Partner with Change and Training leadership to embed communications, role-based enablement, safe-use guidance, feedback loops, and adoption measures into funded initiatives.
Support divisional champion models and strengthen local ownership of outcomes, utilization, workflow change, and sustained business impact.
Coordinate launch- and scale-readiness reviews to ensure capabilities can be adopted safely and sustainably.