Sr / Principal Product Manager - AI Agent Products

Workday•Pleasanton, CA

15h•Hybrid

About The Position

Workday Agent Factory builds on Workday's trusted systems of record, deep finance and HCM workflow context, and enterprise distribution to create autonomous AI agents that can move beyond demos into business-critical work. We operate like a 0-to-1 product team inside Workday: finding high-conviction bets, validating them with real customers, and scaling them into production-grade enterprise products. Our PMs are builders. They work directly with engineering and go deep into customer workflows where data, knowledge, analytics, and AI intersect. We move quickly, but in domains where trust, auditability, compliance, security, and deeply embedded business processes matter. We are hiring Senior and Principal Product Managers to own AI agent products from the earliest bet through GA and scale. This is a hands-on product-building role: you will turn ambiguous customer problems into prototypes, evals, launch scopes, and shipped products with engineering, design, data science, field, and domain teams. The best candidates will be hands-on with agent workflows, customer discovery, product instrumentation, evals, failure modes, and launch execution. You do not need years with the title "AI PM," but you do need to learn new technical domains quickly, build instead of wait, and turn ambiguity into shipped customer value. In your first six months, you will shape a product thesis, validate it with design partners, and define the evidence and scope needed for GA.

Requirements

8+ years of product management, founder, product lead, or equivalent product-building experience for Senior Product Manager; 11+ years for Principal Product Manager.
5+ years building B2B or enterprise software where AI/ML, data, analytics, or decision-support products are central to the customer value proposition.
Track record of 0-to-1 product development: you have taken something from concept to first customers, revenue, or measurable business impact.
Demonstrated technical fluency with AI/ML systems, data or analytics products, enterprise platforms, or workflow automation.
Experience using customer evidence, product metrics, and structured judgment to make high-stakes product decisions with incomplete information.
High agency with modern AI tools: you use tools such as Claude, Cursor, Codex, or equivalents to prototype, analyze, write, test, research, or automate parts of your own product workflow.

Nice To Haves

Hands-on experience building, prototyping, or shipping AI agents, AI-native products, LLM features, workflow automation, decision-support systems, or data-intensive enterprise products.
Strong intuition for agent evaluation, reliability, hallucination risk, human-in-the-loop design, permissions, auditability, and production failure modes.
Experience in regulated or complex domains such as finance, HCM, healthcare, legal, planning, analytics, or enterprise operations.
Experience managing design partner, beta, Early Adopter, or lighthouse customer programs.
Strong product taste: you can simplify complex workflows into opinionated experiences that customers understand, trust, and adopt.
You are already building with AI, whether at work, through side projects, prototypes, internal tools, or hands-on experimentation.
You have strong opinions about where agents should act autonomously, where humans must stay in control, and how to prove the difference.
You are candid about tradeoffs, including projects you killed, launches that missed, or bets that changed direction because the evidence demanded it.

Responsibilities

Own an AI agent product end-to-end, from opportunity discovery and product thesis through GA launch, adoption, and iteration.
Identify and validate high-ROI opportunities in finance and HCM by working backward from real customer pain, business value, data availability, knowledge quality, and failure tolerance.
Partner deeply with engineering to shape reliable agent architectures, evaluation harnesses, observability, human-in-the-loop controls, and production readiness.
Define product-quality evals that measure whether an agent is useful, trustworthy, and ready for customer use, not just whether a demo looks impressive.
Build conviction through working demos, measurable results, customer discovery, design partner programs, and clear decision memos, not polished roadmap theater.
Rally domain PMs, design, engineering, field, legal, security, and executives around the decisions needed to ship.