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New York Life Insurance Co. seeks a Senior Technical Product Manager within TDAV to own the Decision Intelligence agenda end-to-end, aligning board priorities with data pipelines, models and architecture.
You will lead a cross-functional pod, partner with engineering and data science, and present to the C-suite, bridging business and technical concerns in a regulated financial services context. Hybrid work arrangement, leadership of a high-ownership team, and the opportunity to shape AI-enabled
Location Designation: 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.
We build intelligence products that help field professionals make better decisions — not static reports or generic dashboards, but purpose-built surfaces that deliver the right context at the point of action. The quality of those surfaces determines whether our work reaches users at all. This role exists because that bar matters, and because getting it right at scale requires someone who can hold the thread from boardroom priorities down to data pipeline behavior.
The Senior Technical Product Manager on this team owns the product agenda for Decision Intelligence end to end: the strategic narrative that earns executive sponsorship, the roadmap that a squad of engineers, data scientists, and designers can actually execute against, and the judgment to know when a technical shortcut is a smart trade-off versus a debt that will sink the product later. You are not translating between business and engineering — you are fluent in both, and you are the person each side trusts to make the call.
This is a leadership role inside a small, high-ownership team embedded in a large enterprise. You will set direction for other product professionals, represent the portfolio to senior leadership, and remain close enough to the technical fabric — data models, APIs, ML outputs, system architecture — to stress-test what your team proposes before it reaches a steering committee. If you want a role that moves fluidly between a whiteboard with engineers and a slide deck for the C-suite, this is the right environment.
Strategic Product Vision & Roadmap Leadership: You will set the multi-year product vision and strategy for the Decision Intelligence portfolio, translating enterprise priorities and field-professional needs into a roadmap that sequences investment across multiple product lines. You hold the standard for what constitutes a defensible bet, and you are the person who can articulate why a strategy will or will not work — backed by evidence, market context, and a clear-eyed view of technical feasibility.
Senior Leadership & Executive Partnership: You will be a primary product voice in front of senior leadership and business stakeholders — framing trade-offs, defending prioritization decisions, and translating technical constraints into business terms that non-technical executives can act on. You are comfortable being the person in the room who says no to a popular idea and yes to an unpopular one, and can back either with a clear rationale.
Cross-Functional Team Leadership: You will lead and grow a cross-functional pod of product managers, designers, engineers, and data scientists — setting working norms, unblocking execution, and coaching more junior product talent. You are accountable for the team's output and its health, and you build the kind of trust that lets you delegate meaningfully rather than review everything yourself.
Technical & Data Fluency: You will partner directly with engineering leads and data scientists on architecture decisions, model design, and data contracts — not as an approver at the end of the process, but as a participant early enough to shape it. You understand system constraints, data quality issues, and model limitations well enough to make credible product trade-offs and to know when a technical concern raised by an engineer should change the plan.
Design Partnership & Validation: You will work closely with design leadership to set UX standards across the portfolio, review and challenge wireframes and prototypes, and ensure user validation happens before teams build at full fidelity. You bring the product, business, and technical perspective to that partnership; design brings systems and visual thinking. Together you set the bar for what ships.
Shared Platform & Reusability Strategy: A core expectation of this role is thinking in platforms, not point solutions. You will set the strategy for shared components, data services, and design patterns that are reused across the full canon of intelligence products, and you will hold other teams accountable to building for reuse rather than rebuilding in isolation.
Data, AI/ML, and Governance: Intelligence products are only as good as the models and data behind them. You will partner with data science and risk/compliance stakeholders to define what \"production-ready\" means for a model-driven surface — accuracy thresholds, explainability requirements, monitoring, and the honest communication of uncertainty to end users, particularly in a regulated financial services context.