Corporate Vice President - Product Delivery and Execution Orchestrator

Hybrid - 3 days per week

Within the Tech, Data, AI, Ventures (TDAV) organization, our work is guided by a shared vision: deploying the power of technology, data, AI and ventures to accelerate sustainable competitive advantage for New York Life's businesses. We build solutions that power how we serve policy owners, agents, advisors and employees while delivering measurable business outcomes.

Across technology, data, AI, cyber, product, digital experience, architecture and infrastructure, TDAV combines the scale and investment of an industry leader, access to leading-edge technologies and the opportunity to help shape how a world-class financial services company competes in the AI era - all backed by the stability and purpose of a mutual company built to last.

Join New York Life's Enterprise Intelligence team as a Product Delivery and Execution Orchestrator on the Enterprise Intelligence team. This role supports AI & Data project teams from ideation through production implementation and business success.

• Drive product delivery:
  Spearhead kickoff, tracking, and progress across the entire analytics product lifecycle. Partner closely with Product Managers, Business Product Managers/Owners, Tech Leads, Analytics Leads, and Product Activation teams to define, create, refine, maintain, and launch analytical products. Guide products from early concept through refinement, prototyping, pilot, broader release, and ongoing maintenance - shaping the work and helping teams move ideas toward mature, scalable delivery.
• Track execution:
  Maintain Asana boards, capture business needs and product feedback, support prioritization and task allocation, map work to upcoming releases, and facilitate standups, business-team cadences, and backlog grooming sessions.
• Maintain reporting and visibility:
  Manage weekly, monthly, and quarterly reporting aligned with current expectations, with an emphasis on business impact and the value of work and features being delivered rather than purely technical updates. Keep key wins, impact slides, and other periodic content current; tailor reporting to the target audience; and provide visibility into progress, impediments, risks, and other areas of importance while helping remove or mitigate barriers to delivery.
• Coordinate release and change management:
  Prepare release management and Service Now documentation in accordance with Technology (TDAV) processes and standards through the TDLC Service Now lifecycle. Coordinate with change teams, impacted parties, and support teams; work to resolve conflicts before deployment; and represent production changes in Change Approval Board meetings as needed.
• Facilitate Product Increment quarterly planning:
  Support adherence to applicable AI & Data planning processes and partner with Product Owners, Tech Leads, and team members to identify and document dependencies during Pre-PI planning. Facilitate dependency discussions, confirm scope, capacity, timelines, and tracking, and support appropriate Enterprise Intelligence participation and representation during PI events and readouts.
• Maintain delivery discipline across teams:
  Ensure JIRA epics, stories, dependency logs, and related tracking remain current and aligned with AI & Data planning processes. Work collaboratively across product and technology teams to clarify dependencies, surface risks and issues, and support consistent execution across products and work streams.

• 6-8 years of experience in technical project management, program management, or Agile delivery management.
• 5+ years of experience in Product ownership or product delivery - working across business and technology teams and able to represent the product seamlessly across both.
• Strong attention to detail with the ability to proactively identify, capture, and communicate risks and issues.
• Ability to collaborate effectively across product, business, data, and technology teams in a fast-paced, team-oriented environment with flexible goals and changing priorities.
• Well-versed in AI/LLM tool usage (Claude, OpenAI, CoPilot, Gemini) to be able to optimize productivity.

• Exposure to cloud data platforms such as GCP, AWS, Databricks, or Big Query.
• Interest in AI, machine learning, and enterprise intelligence applications.
• Experience with dbt or similar transformation tools.
• Familiarity with data architecture, data warehousing concepts, and analytics best…