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Vice President, Data & AI Platforms

Job in Newark, Essex County, New Jersey, 07175, USA
Listing for: Relha LLC
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Cloud Computing, AI Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability, and efficiency? The Global Technology and Operations team takes great pride in our culture where digital transformation is built into our DNA! When you join our organization at Prudential, you’ll unlock an exciting and impactful career – all while growing your skills and advancing your profession at one of the world’s leading financial services institutions.

Your

Team & Role

As you will play a critical enterprise leadership role within Global Technology. You will own the strategy, governance, and delivery of Prudential’s enterprise data and AI platforms, including the central platform, AI/ML platform, data platforms, data engineering, enterprise data management, modeling, analytics operations, and supporting tooling and shared services.

This role is accountable for platform vision, roadmap, investment alignment, and operational excellence—ensuring platforms scale securely, reliably, cost‑effectively, and consistently across the enterprise. You will oversee ML operations (MLOps), data operations, engineering operations, Fin Ops, and platform site reliability engineering (SRE) as core enterprise capabilities.

In close partnership with the CTO, you will lead the enterprise data and AI platform organization as responsibilities evolve with the operating model. You will define core capabilities, shared frameworks, and operational standards that enable reuse, interoperability, reliability, and secure self‑service across business units.

This role requires deep collaboration with business functions, enterprise architecture, infrastructure, security, and application technology teams. We are seeking a leader who combines strong technical depth with enterprise product and operational leadership—someone who can translate strategy into scalable platforms, align diverse stakeholders, and build high‑performing engineering organizations.

What You Can Expect on a Typical Day

Define and own the enterprise vision, strategy, and roadmap for data, AI/ML, and central platforms, aligned to Prudential’s business, data, AI, and technology strategies.

Lead enterprise platform engineering, including the central platform, AI/ML platform, and data platforms, encompassing architecture, engineering, and modernization efforts.

Centrally manage core data and AI platforms and shared services, driving consistency, reuse, scalability, operational maturity, and adoption across business units and functions.

Oversee ML Operations (MLOps) to ensure reliable model development, deployment, monitoring, and lifecycle management at enterprise scale.

Establish and lead data operations and engineering operations, including platform support models, run‑time stability, on‑call practices, and continuous improvement of delivery and operational metrics.

Own platform SRE capabilities, ensuring resilience, availability, performance, incident management, and platform observability across data and AI platforms.

Lead Fin Ops practices for data and AI platforms, including cloud cost visibility, optimization, forecasting, and investment alignment in partnership with finance and infrastructure teams.

Oversee enterprise data and AI applications (e.g., Enterprise Data Platform), partnering closely with Division Technology Leaders to ensure alignment, value realization, and responsible platform usage.

Manage enterprise data and AI tooling and services, including marketplace capabilities, data catalog, Model Ops tooling, and CDO operational platforms.

Establish and govern enterprise standards, policies, and controls for data and AI platforms, services, and tooling, ensuring alignment with information security, risk, and compliance requirements.

Partner with Enterprise Architecture to define and evolve reference architectures, solution patterns, and shared frameworks for data and AI platforms.

Define and enable self‑service platform capabilities that expand access to approved data and AI features while maintaining governance, reliability, and controls.

Liaise with platform and tooling vendors to evaluate, procure, and manage enterprise capabilities,…

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