Vice President, Data & AI Engineering

About the role

Job Classification: Technology - Agile, Delivery, & Product Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability, and efficiency? The Global Technology team takes great pride in our culture, where digital transformation is built into our DNA. When you join Prudential, you'll unlock an exciting and impactful career - while growing your skills and advancing your profession at one of the world's leading financial services institutions. Your Team & Role As the Vice President, Data & AI Engineering, reporting to the Chief Data & AI Officer, you will lead Prudential's forward deployed data and AI engineering organizations responsible for building, scaling, and operationalizing trusted, AIready data products across the enterprise.Your organization functions as Prudential's front‑line delivery engine for data and AI, deploying elite engineering teams to the company's highest‑priority business initiatives. Rather than permanently embedding within a single domain, these teams rotate across business areas - accelerating delivery, compounding institutional knowledge, and ensuring consistent engineering standards across the enterprise. Your scope includes Data Engineering, AI Engineering, Machine Learning Engineering (including MLOps and LLMOps), Agentic Engineering, Conversational AI, Intelligent Automation (including RPA and workflow automation), BI & Analytics Engineering, DataOps, and Data Product Certification. You are accountable for translating advanced analytics and AI capabilities into measurable business outcomes, while balancing speed and innovation with enterprise reliability, security, and responsible AI. In this role, you will partner closely with senior business leaders, product teams, architecture, governance, risk, legal and compliance, security, workforce, and platform leaders to ensure data and AI investments deliver sustained enterprise value. This role requires deep technical judgment, strong delivery leadership, and the ability to mobilize highly skilled engineering teams against Prudential's most complex, high‑impact AI‑driven opportunities. What You Can Expect on a Typical Day Lead and scale forward‑deployed data and AI engineering acceleration teams that rotate across business domains to deliver high‑impact, production‑ready solutions aligned to enterprise priorities. Own the end‑to‑end engineering execution of data, AI, and machine learning solutions - from domain onboarding and data sourcing through certification, production deployment, and operationalization. Serve as the senior engineering leader accountable for delivery quality, technical rigor, and production reliability across data engineering, AI engineering, ML engineering, agentic systems, BI & analytics, and intelligent automation. Deploy specialized engineering teams to complex, ambiguous business problems, rapidly designing and implementing solutions that reduce time‑to‑value and deliver measurable outcomes. Oversee the certification and operationalization of Authorized Data Sources and AI‑ready data products, ensuring data quality, lineage, access control, audit readiness, and agent‑readiness standards are met. Establish and reinforce AI‑assisted engineering practices, embedding AI tooling into the development lifecycle to materially increase engineering productivity and velocity. Partner closely with business leaders and transformation sponsors to translate strategic priorities into executable engineering roadmaps and delivery plans. Collaborate with platform, architecture, security, and governance leaders to ensure solutions are engineered in alignment with enterprise standards while maintaining delivery speed. Ensure AI and data solutions are built with operational readiness in mind, including monitoring, observability, incident management, and post‑deployment support as teams rotate to new domains. Provide hands‑on technical leadership and act as an escalation point for complex engineering decisions, delivery risks, and design tradeoffs. Communicate engineering progress, risks, and outcomes clearly to executive stakeholders, enabling informed prioritization and investment decisions. Build and sustain a high‑performance, inclusive engineering culture focused on craftsmanship, continuous learning, accountability, and mission‑driven execution. The Skills & Expertise You Bring Bachelor's degree in computer science, engineering, or a related field; advanced degree preferred. Extensive experience leading large‑scale data and AI engineering organizations in complex, enterprise environments. Deep, hands‑on expertise across data engineering, AI engineering, machine learning engineering, and analytics, with a strong understanding of how these capabilities come together in production. Proven track record of delivering production‑grade data and AI solutions that drive real business outcomes - not just pilots or proofs of concept. Strong technical fluency