Data & AI Technology Delivery Lead - Vice President

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Prin Technology Admin Office position at the Vice President Level, which is part of the job family responsible for managing administrative tasks related to technology infrastructure and services, ensuring smooth operations and support for the organization’s technology needs.

The Data & AI Technology Delivery Lead is a hybrid technology leadership role combining Fleet Enablement, Service Delivery Management, program execution, and Data & AI domain leadership.

The role is responsible for translating the Data & Analytics strategy into coordinated execution across engineering teams, product owners, infrastructure partners, control functions, business stakeholders, and strategic vendors. The individual will provide centralized ownership of planning, prioritization, delivery governance, stakeholder communication, and operational readiness across the Data & AI platform portfolio.

Unlike a traditional project-management role, this position requires sufficient technical depth to understand enterprise data platforms, AI capabilities, architecture dependencies, production-readiness requirements, and governance controls. The individual will act as the connective layer between technology strategy and execution, ensuring that priority capabilities move from evaluation through approval, onboarding, and production adoption.

This role builds on the established Fleet Enablement model, which includes roadmap alignment, dependency management, blocker removal, fleet ceremonies, metrics, external-partner engagement, and continuous improvement

What you’ll do in the role:

1. Fleet Enablement and Strategic Execution

• Partner with Fleet and technology leadership to translate strategic priorities into structured roadmaps, bodies of work, milestones, and measurable outcomes.
• Coordinate planning and execution across Data & Analytics squads, product teams, operations, architecture, cybersecurity, legal, procurement, and control functions.
• Maintain an integrated view of priorities, dependencies, capacity constraints, delivery risks, and critical decisions.
• Facilitate fleet-level governance and operating forums, including roadmap reviews, leadership updates, planning sessions, and cross-product working groups.
• Identify and remove organizational, technical, or process blockers that affect delivery.
• Promote consistent execution practices and continuous improvement across the fleet.
• Ensure squads remain aligned to approved priorities, roadmaps, and key performance indicators.

These responsibilities align with the Fleet Enablement framework’s expectations for managing dependencies, removing blockers, facilitating ceremonies, tracking metrics, supporting roadmap delivery, and collaborating with external partners

2. Service Delivery Management

• Serve as a central point of accountability for the delivery and ongoing operation of Data & AI platform capabilities.
• Establish and maintain transparent intake, prioritization, planning, and delivery-tracking processes.
• Manage and prioritize work across platform hygiene, core functionality, service improvements, control remediation, client onboarding, and strategic AI enablement.
• Track commitments, milestones, risks, incidents, dependencies, remediation actions, and production-readiness requirements.
• Coordinate delivery across engineering teams, product owners, infrastructure partners, vendors, and internal clients.
• Provide clear escalation of delivery risks, resource constraints, service issues, and decisions requiring leadership attention.
• Support service governance, lifecycle management, capacity planning, operational readiness, resilience, and control obligations.
• Balance strategic change with operational stability, regulatory requirements, and platform sustainability.

3. Data & AI Technology Leadership

• Provide technology leadership across enterprise data, analytics, and AI platforms, including cloud data platforms, BI and analytics, data integration, and AI-enabled engineering solutions.
• Develop a working understanding of platform architectures, capabilities, limitations, governance requirements, and production-readiness dependencies.
• Translate business and technology requirements into actionable delivery plans for engin…