Vice President Product Management: Decision Intelligence Platform

Workday•Pleasanton, CA

3d•Hybrid

About The Position

Workday is a Fortune 500 company and a leading AI platform for managing people, money, and agents, shaping the future of work. The Decision Intelligence Platform team is an integrated Product and Engineering organization within Workday’s Planning Business Unit, owning all components of the “DecisionOS.” This role is for an AI-native product leader ready to scale a business and organization around AI and agentic systems, with the singular mandate to realize the Decision Intelligence Platform. The goal is to deliver customer-validated Decision Intelligence use case flows, drive adoption, and establish Workday as the leader in AI-powered planning and analytics, while earning the trust of finance buyers in deterministic, audit-driven environments.

Requirements

12+ years in Product and/or Engineering management, including substantial experience leading product and engineering teams.
At least 3 years building AI/ML or agentic products where AI is the core value proposition.
Strong product and organizational leadership.
Deep, current fluency in modern AI systems and a demonstrated ability to evolve quickly with a fast-changing technology and market landscape.
Fluent in the architecture of agentic systems, LLMs, semantic reasoning, MCP/A2A, Human-in-the-Loop design, and AI evaluation frameworks.
Ability to partner credibly with engineers on system design and make informed tradeoffs between model performance, latency, cost, and trust.
Ability to convert complex business objectives into hypothesis-driven experiments, formal evaluation plans, telemetry instrumentation, and platform-aware roadmaps.
Ability to discuss packaging tiers, consumption models, and sales motions.
Understanding that "building it" is only half the job; "selling the transition" is the other half.
Familiarity with Finance, FP&A, or enterprise planning buyers preferred.
Strong comfort navigating deterministic, audit-driven enterprise environments where trust and governance are non-negotiable.
Demonstrated ability to recruit, develop, and lead a high-performing AI-native product team.
Experience managing managers strongly preferred.
Experience designing or contributing to native cloud applications at scale.
BA/BS degree required.

Nice To Haves

Advanced degree in a technical or quantitative field preferred.

Responsibilities

Own the full lifecycle of Decision Intelligence use case flows — from problem discovery through design partner selection, iterative build, and production deployment.
Drive the product strategy and execution for the Planning Agent (including skills for Data Exploration, Variance Analysis, Scenario Planning, KPI Monitoring, and Self-Service).
Define the boundary between governed planning and ungoverned exploration, and ensure seamless handoff between the two.
Run hypothesis-driven development with formal evaluation plans, telemetry instrumentation, and fast iteration loops.
Partner with leaders across Workday and within the Planning Business Unit to define how we monetize Decision Intelligence.
Own the product side of the Adaptive Planning Pro subscription, including tiered packaging, Flex Credit economics, and value-based pricing models.
Partner with Product Marketing and Sales to define the narrative, equip the field with proof points and reference customers, and demo flows needed to close early customers and drive meaningful ACV.
Drive enterprise ecosystem integration via MCP/A2A, enabling Decision Intelligence to show up in Sana, third-party agent platforms, and customer workflows wherever decisions are made.
Build the guardrails, audit trails, and observability frameworks that give CFOs confidence to adopt these tools.
Ensure every agent action is traceable, explainable, and bounded.
Leverage Workday's ISO-certified Responsible AI framework to ensure Decision Intelligence capabilities meet security, compliance, and auditability standards.
Lead an integrated Product and Engineering team as a player-coach, driving end-to-end ownership and accountability.
Build a team of AI-native product managers who think in hypotheses, evals, and telemetry.
Identify skill gaps, recruit AI talent, and create the operating cadence for a high-velocity AI product organization.