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About This Role
Job descriptionCompany and benefits
Job IDPRINC017366
Employment TypeRegular
Work Stylehybrid
LocationSunrise,FL,United States, Lowell,MA,United States
TravelUp to 25%
RolePrincipal Product Manager, our UKG Bryte AI PlatformWhy UKG:
At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform. Helping people get paid, grow in their careers, and shape the future of their industries. That’s what we do.
We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters—and so do you.
About the Role
We’re looking for a Principal Product Manager to own and evolve Bryte’s AI platform, including assistive and agentic AI capabilities used across UKG products. This role is for someone who is hands\-on, comfortable operating without formal authority, and able to drive outcomes through clarity, judgment, and execution.
You’ll work across engineering, AI services, UX, GTM, and leadership to turn ambiguous problems into shipped products. This is not a strategy\-only role; you’ll be close to the work and accountable for the results.
What You’ll Do
- Own product strategy and execution for the Bryte AI platform capabilities (assistive experiences, agents, SDKs, shared services).
- Translate complex customer and business problems into clear requirements, priorities, and roadmaps.
- Drive delivery across multiple teams and dependencies, even when no one reports to you.
- Partner closely with engineering and AI teams to make pragmatic tradeoffs on scope, quality, speed, and risk.
- Write clear PRDs, decision docs, and status updates that don’t need follow\-ups.
- Use customer feedback, usage data, and telemetry to guide iteration and decisions.
- Surface risks early, propose solutions, and follow through.
- Communicate effectively across levels: engineers, partners, and senior leaders.
What Success Looks Like
- Teams are aligned and moving without constant escalation.
- Engineers trust your product judgment and clarity.
- Stakeholders understand priorities and tradeoffs.
- AI features ship, are adopted, and deliver real customer value.
Required Qualifications
- 5–8\+ years of Product Management experience in enterprise SaaS.
- Experience shipping AI\-powered products (Agentic AI experience, GenAI, copilots, conversational UX, agents, or automation).
Expected skills and abilities
- Comfortable working across technical and non\-technical audiences.
- Proven ability to lead through influence and operate across teams.
- Even\-keeled, reliable, and calm under pressure.
- Quick to grasp new domains and concepts.
- Strong ownership mindset; takes action and closes loops.
- Excellent written and verbal communication.
Nice to Have (not required)
- Platform experience.
- Experience with AI evaluation, trust, or compliance considerations.
- Background working in regulated or complex enterprise environments.
This is NOT for You if
- Prefer narrowly defined problems with minimal ambiguity.
- Need formal authority to move work forward.
- Avoid execution details or hands\-on problem solving.
Company Overview:
UKG is the Workforce Operating Platform that puts workforce understanding to work. With the world's largest collection of workforce insights, and people\-first AI, our ability to reveal unseen ways to build trust, amplify productivity, and empower talent, is unmatched. It's this expertise that equips our customers with the intelligence to solve any challenge in any industry — because great organizations know their workforce is their competitive edge. Learn more at ukg.com.
Equal Opportunity Employer
Equal Opportunity Employer
UKG is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, disability, religion, sex, age, national origin, veteran status, genetic information, and other legally protected categories.
View The EEO Know Your Rights poster
UKG participates in E\-Verify.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Disability Accommodation in the Application and Interview Process
For individuals with disabilities that need additional assistance at any point in the application and interview process, please email UKGCareers@ukg.com.
The pay range for this position is $163,900\.00 to $235,550\.00\. The actual base pay offered may vary depending on skills, experience, job\-related knowledge and work location. In addition to base pay, employees may be eligible to participate in a performance\-based bonus plan and to receive restricted stock unit awards as part of total compensation. Learn more about UKG’s benefits and rewards at https://www.ukg.com/about\-us/careers/benefits
NOTICE ON HIRING SCAMS
UKG will never ask you for a copy of your driver’s license, social security card, or passport during a job inter
ABOUT OUR JOB DESCRIPTIONS
All job descriptions are written to accurately reflect the open job and include general work responsibilities. They do not present a comprehensive, detailed inventory of all duties, responsibilities, and qualifications required for the job. Management reserves the right to revise the job or require that other or different tasks be performed if or when circumstances change.
Salary Context
This $163K-$235K range is above the median for AI Product Manager roles in our dataset (median: $174K across 475 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 26,159 AI roles we're tracking, AI Product Manager positions make up 2% of the market. At UKG, 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 Required
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 $204,600 based on 532 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $163K to $235K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
UKG AI Hiring
UKG has 3 open AI roles right now. They're hiring across Data Scientist, AI Architect, AI Product Manager. Positions span Weston, FL, US, San Francisco, CA, US, Lowell, MA, US. Compensation range: $186K - $335K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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