Vice President Product Management Decision Intelligence Platform

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About the Team

About the Role

The Opportunity: Building the Decision Intelligence Platform

Workday Adaptive Planning with over 7000 customers worldwide is Workdays flagship product for financial and HR planning. 20 years ago Adaptive disrupted the established EPM category by moving it to the Cloud. Today thanks to the transformational power of AI were doing it again by creating a new category and multi-billion dollar market: Decision Intelligence. FP&A is shifting from data wrangling and reporting to continuous decision orchestration. Our mission is to deliver an agentic planning and analytics platform that enables everyone to navigate any decision domain with confidence.

The Role: AI-Native Product Leader

We are looking for an AI-native product leader who is ready to take the next step someone who has gone deep into AI and agentic systems and is now ready to scale a business and organization around them. This is a focused singular mandate: realize the Decision Intelligence Platform. You will lead an integrated Product and Engineering team to deliver customer-validated Decision Intelligence use case flows drive adoption and establish Workday as the leader in AI-powered planning and analytics. Your job is to build the future fast while earning the trust of finance buyers who operate in deterministic audit-driven environments.

Responsibilities

Your mandate is concentrated on delivering and scaling the Decision Intelligence Platform:

1. Deliver Customer-Validated Decision Intelligence Workflows

End-to-End Use Case Ownership: Own the full lifecycle of Decision Intelligence use case flows from problem discovery through design partner selection iterative build and production deployment. Customers will not reward us for capabilities; they will reward us for end-to-end outcomes.

Roadmap & Strategy: 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.

Rapid Experimentation: Run hypothesis-driven development with formal evaluation plans telemetry instrumentation and fast iteration loops. Move from demo to proven value quickly.

2. Drive Commercial Success

Commercial Architecture: 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 that capture the ROI of agentic planning.

GTM Partnership: 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.

MCP/A2A & Ecosystem: 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.

3. Build Trust for AI in Finance

Governance & Observability: You are introducing probabilistic AI into deterministic Finance. 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.

Responsible AI: Leverage Workdays ISO-certified Responsible AI framework. Ensure that Decision Intelligence capabilities meet the security compliance and auditability standards enterprise finance demands.

4. Build and Lead the Team

Integrated Team Leadership: Lead an integrated Product and Engineering team as a player-coach. Drive end-to-end ownership and accountability fewer handoffs faster decisions tighter product-architecture coupling.

AI-First Culture: Build a team of AI-native product managers who think in hypotheses evals and telemetry not feature specs and waterfall releases. Identify skill gaps recruit AI talent and create the operating cadence for a high-velocity AI product organization.

About You

• The ideal candidate is an AI-native product leader who has built and shipped agentic or AI-first products and is ready to scale their impact at enterprise level. You combine deep technical fluency in AI systems with the commercial instincts and leadership maturity to build a business not just a product.
• AI Product Leadership: 12 years in Product and/or Engineering management including substantial experience leading product and engineering teams and at least 3 years building AI/ML or agentic products where AI is the core value proposition. You pair strong product and organizational leadership with deep current fluency in modern AI systems and a demonstrated ability to evolve quickly with a fast-changing technology and market landscape.
• Technical Depth: Fluent in the architecture of agentic systems LLMs semantic reasoning MCP/A2A Human-in-the-Loop design and AI evaluation frameworks. You can partner credibly with engineers on system design and make informed tradeoffs between model performance latency cost and trust.
• Hypothesis-Driven Development: Converts complex business objectives into hypothesis-driven experiments formal evaluation plans telemetry instrumentation and platform-aware roadmaps. You prove value before scaling.
• Commercial Instincts: Can discuss packaging tiers consumption models and sales motions. Understands that building it is only half the job; selling the transition is the other half.
• Finance / Enterprise Domain Affinity: Familiarity with Finance FP&A or enterprise planning buyers preferred. At minimum strong comfort navigating deterministic audit-driven enterprise environments where trust and governance are non-negotiable.
• Team Building: Demonstrated ability to recruit develop and lead a high-performing AI-native product team. Experience managing managers strongly preferred.
• Cloud Architecture Literacy: Experience designing or contributing to native cloud applications at scale.
• Education: BA/BS degree required; advanced degree in a technical or quantitative field preferred.

Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidates compensation offer will be based on multiple factors including but not limited to geography experience skills job duties and business need among other things. For more information regarding Workdays comprehensive benefits please click here.

Additional Considerations:

Our Approach to Flexible Work

With Flex Work were combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections maintain a strong community and do their best work. We know that flexibility can take shape in many ways so rather than a number of required days in-office each week we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers prospects and partners (depending on role). This means youll have the freedom to create a flexible schedule that caters to your business team and personal needs while being intentional to make the most of time spent together. Those in our remote home office roles also have the opportunity to come together in our offices for important moments that matter.

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