Principal Product Manager - Workday AI - Agent Factory

Workday•Vancouver, BC

2d•$196,000 - $294,000•Hybrid

About The Position

Workday Agent Factory builds autonomous AI agents that become standalone product lines, not incremental AI features bolted onto existing workflows. We operate as a 0-to-1 team inside Workday: identifying high-conviction bets in complex, regulated domains like finance and HCM, then building production-grade agents that will become revenue lines. Our PMs prototype with their own hands, ship fast, and navigate the real constraints of enterprise customers: compliance, auditability, and deeply embedded business processes. If you want to build the next generation of enterprise software, not just add AI to the current one, this is the team. We are looking for Principal Product Managers who have shipped production AI agent systems and want to do it again at enterprise scale. You will own an agent from concept through GA: scoping the bet, prototyping solutions, running early adopter programs, and scaling to Workday's global customer base. This is not a strategy-deck role. You will be hands-on with agent architectures, evaluation frameworks, and customer workflows daily, while also making sharp prioritization calls across a fast-moving portfolio. This role requires a rare combination: the scrappiness to prototype and build in weeks, the technical depth to design reliable agent systems, and the domain judgment to solve real problems in highly regulated, highly complex environments.

Requirements

11+ years of product management experience
5+ years in SaaS/B2B enterprise software
Direct experience building and shipping external, revenue generating AI forward product and /or agent systems to production (not just AI/ML features, but agents that reason, plan, and take action autonomously)
Deep technical acumen: you can evaluate agent architectures, debug failure modes, and make informed design tradeoffs with engineering
Strong communication and relationship-building skills across engineering, customers, and executive stakeholders

Nice To Haves

Experience in regulated or complex domains (finance, HCM, healthcare, legal) where trust, compliance, and auditability are non-negotiable
Track record of 0-to-1 product development: you've taken something from idea to revenue, not just maintained an existing product
Bias for action, comfortable making high-stakes decisions with incomplete information and iterating from there
Experience managing Early Adopter or beta programs with enterprise customers
Ability to operate across multiple functions, influence senior executives, and drive alignment without authority
You are already building agent systems, whether prototyping on weekends, shipping side projects, or pushing the boundaries at your current company
You have strong opinions on agent evaluation, reliability, and human-in-the-loop design, formed from hands-on experience, not just reading papers
You learn complex customer domains fast and can identify where agents create step-function value versus where they create risk
You are motivated by building new product lines from scratch, not optimizing existing ones
You are organized enough to track dozens of moving pieces across customers, engineering, and stakeholders while maintaining velocity

Responsibilities

Own an AI agent end-to-end, from identifying the opportunity through GA launch and beyond
Prototype and validate agent concepts rapidly, using real customer workflows and data to pressure-test viability before committing engineering resources
Design production-quality agent systems in collaboration with engineering, ensuring reliability, auditability, and trust in regulated domains
Run customer discovery and Early Adopter programs to validate value, generate references, and derisk at every stage
Identify the highest-ROI agent opportunities in finance and HCM, build conviction with data, and advocate for them within the organization
Define measurable value outcomes and evaluation frameworks that prove agent impact quantitatively
Collaborate deeply with domain PMs to understand workflows, constraints, and where autonomous agents unlock step-function value versus incremental improvement
Communicate agent vision and progress to executives, customers, field teams, and implementers, translating technical capability into business value