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Your work days are brighter here.
We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun\-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.
About the Team
The Core Financial Accounting Product Management team at Workday is at the center of how we bring AI into the Office of the CFO. We empower customers with intuitive experiences, continuous innovation, and AI\-driven business compliance and operational efficiency across Workday Financials.
Workday Financials is a product organization that is always evolving. We are a team of product\-minded technologists who are passionate about making life better for finance professionals and everyone who interacts with the Office of the CFO. We partner closely with the Agent Platform and broader AI teams to design and deliver agentic, AI\-powered experiences on top of our Core Financials foundation.
We use AI tools such as Cursor and large language models to build finance\-focused agent skills that help customers automate repetitive work, improve decision quality, and unlock new insights. If you enjoy collaborating with a supportive team that is always looking for fresh ways to innovate with new tools, frameworks, and processes, this is a great place to grow your career.
About the Role
As a Senior Product Manager for Core Financials AI, you will lead the definition and delivery of AI\-powered capabilities and agent skills that transform how finance teams use Workday Financials. You’ll sit at the intersection of AI and accounting: owning AI use cases that span core accounting workflows, and ensuring they are understood, trusted, and adopted by customers at scale.
You will either build finance\-focused, customer\-facing agents on top of Workday’s Agent Platform or define the underlying capabilities and patterns that help application teams bring Core Financials AI skills to market quickly and consistently. You’ll work at high velocity with machine learning, engineering, AI platform, and financials domain product partners to turn emerging AI techniques into clear product narratives, scalable solutions, and measurable business outcomes.
This role calls for strong product judgment, deep curiosity about AI and agentic systems, and a genuine interest in financial workflows. You will help define how Workday positions, builds, and delivers next\-generation Core Financials with AI and agents—ensuring innovation lands with clarity, credibility, and purpose for the Office of the CFO.
About You
In this role, you will be responsible for:
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- Owning the vision, strategy, and roadmap for AI\-powered capabilities and agent skills within Core Financials, grounded in the needs of CFOs, controllers, and accounting teams
- Identifying the highest\-impact, highest\-ROI AI opportunities in Core Financials, advocating for them within Workday, and building or enabling other teams to build these capabilities
- Partnering with AI and Agent Platform teams to design secure, governed, and trustworthy agentic experiences tailored to financial use cases
- Developing a deep understanding of Workday Core Financials and adjacent products, and using that knowledge to define AI/agent use cases that are technically feasible and financially meaningful
- Working closely with engineering, ML, UX, and content teams to define product requirements, experiment with AI/LLM\-powered solutions, and ship production\-grade features—not just prototypes
- Interfacing with customers to run discovery, validate concepts, and operate early adopter/validation programs that de\-risk AI investments and ensure customer value and referenceability
- Defining value outcomes and success metrics for Core Financials AI investments, and using data and research to inform prioritization and iteration
- Partnering with other product teams across Financials and the wider Workday portfolio to ensure agent skills compose well, respect controls and compliance needs, and feel cohesive across experiences
- Acting as the product champion for Core Financials AI: clearly communicating the vision, roadmap, and new capabilities to internal stakeholders, field teams, and customers
- Mentoring and coaching other product managers who are exploring AI and agent use cases in financial domains, and helping to uplevel AI product practices across the team
About You
Basic Qualifications
- 5\+ years of experience in product management, including end\-to\-end ownership of product or feature lifecycles
- 5\+ years of experience with SaaS/B2B products
- Technically proficient (even if not a coder) with AI and LLM\-powered technology (e.g., understanding agent architectures, LLM capabilities/limitations, prompt patterns, and evaluation approaches)
- Experience as a product owner, enterprise financials systems analyst, or functional consultant working on ERP, financial management, accounting, or closely related financial systems
Other Qualifications
- Skilled in decision making and creative problem\-solving, with the ability to evaluate complex situations, weigh trade\-offs, and select the best course of action from multiple alternatives. You bring creativity and sound judgment to ambiguous challenges and develop proactive solutions that move the product and team forward.
- Demonstrated strength in cross\-team collaboration and operational coordination, with experience leading complex initiatives across multiple functions (e.g., ML, platform, application product teams, and go\-to\-market). You are organized, capable of tracking many moving pieces, and can bring together diverse teams to deliver results on time and with quality.
- Experienced in business influence, with the ability to synthesize complex inputs—from finance stakeholders, AI platform constraints, and customer feedback—into a compelling AI product strategy and direction for Core Financials. You build buy\-in from team members, contributors, and partners, and you can articulate a clear vision.
- Comprehensive understanding of the reporting and analytics needs of the Office of the CFO, and how AI and agents can augment tasks like close, reconciliation, reporting, and analysis.
- Passionate about following the latest in AI products and emerging technologies, with hands\-on experience exploring and experimenting with tools such as large language models, retrieval\-augmented generation, and agent frameworks.
- Strong data analysis skills: you use product analytics, usage data, and qualitative research to derive actionable insights that inform AI use\-case selection, prioritization, and iteration, and to measure the impact of AI features in production.
- Comfortable engaging in technical discussions with engineering and ML partners (e.g., trade\-offs between retrieval vs. fine\-tuning, safety/guardrail approaches, performance and cost considerations), even if you are not writing code day\-to\-day.
- A deeply empathetic customer advocate with a history of understanding complex customer pain points quickly based on public information, internal data, and customer conversations—and translating them into differentiated AI\-powered experiences for enterprise users.
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 candidate’s 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 Workday’s comprehensive benefits in Canada, please click here . For more information regarding Workday’s comprehensive benefits in the US, please click here .
Primary Location: USA.CA.Pleasanton
Primary Location Base Pay Range: $168,000 USD \- $252,000 USD
Additional CAN Location(s) Base Pay Range: $135,700 \- $203,500 CAD
Our Approach to Flexible Work
With Flex Work, we’re 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 you'll 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.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email [email protected] .
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Salary Context
This $135K-$252K range is above the median for AI Product Manager roles in our dataset (median: $188K across 140 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Workday, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills in Demand for This Role
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $216,175 based on 270 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($193K) sits 10% below the category median. Disclosed range: $135K to $252K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Workday AI Hiring
Workday has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Pleasanton, CA, US, Reston, VA, US. Compensation range: $205K - $370K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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