Principal PM, Enterprise AI & Productivity

HR Tech Job

Pleasanton (CA)

Hybrid

USD 196,000 - 294,000

Full time

2 days ago

Be an early applicant

Application generator

Don’t send a generic resume — generate a resume and cover letter tailored to this exact role.

Get past ATS filters

Job summary

Workday seeks a highly strategic Principal Product Manager to shape digital work experiences. You will own vision, strategy, roadmap, and outcomes for enterprise productivity and collaboration tools used by Workday's global workforce.

You will lead initiatives across governance, security, and AI-enabled analytics, partnering with stakeholders, engineering, and executives to deliver scalable, secure product experiences aligned with company goals.

Qualifications

Experience delivering employee-facing digital products such as intranets, mobile apps, collaboration platforms, or chatbots.
Experience deploying or managing enterprise SaaS capabilities and productivity tools.
AI domain fluency with practical understanding of governance and governance considerations.
Ability to evaluate vendor or SaaS platforms against business requirements, security, privacy and ROI criteria.
Proven ability to use data, analytics and qualitative feedback to drive product improvements.
Strong business-case development and ROI modeling skills.
Deep understanding of UX principles and translating needs into effective workflows.
Exceptional executive communication and stakeholder management skills.
Track record of leading through ambiguity and driving accountability.

Responsibilities

Establish and own a compelling product vision and strategic roadmap aligned to the company vision and priorities.
Lead strategic engagements with stakeholders to define problems, build alignment, and develop ROI models.
Define and measure product success through KPIs like adoption, usage, and efficiency.
Be the voice of the customer for employees and stakeholders, identifying pain points and opportunities.
Leverage AI and analytics to translate feedback and trends into value hypotheses.
Prioritize features, technical debt reduction, and vendor capabilities based on value and risk.
Translate initiatives into clear requirements, user stories, acceptance criteria, and release plans.
Collaborate with engineering and cross-functional teams to drive discovery, design, and execution.
Maintain current knowledge of AI capabilities and enterprise SaaS practices.