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About This Role
Overview:
PeopleReady is expanding its BI, ML, and AI capabilities to help achieve the organization's long-term objectives. We're looking for an experienced Sr. Product Manager to help build and manage our AI Service offerings. You will act as the conduit between the business and technology teams, balancing strategic priorities with system stability and defining complex data-related requirements. You’ll be the champion of product-led AI, including large language model (LLM) and Data Science/Machine Learning applications, the platforms and APIs that deliver them, and our Data Analytics and Business Intelligence initiatives.
If you have the drive to build incredible, data and insights-driven products that impact the lives of our customers and associates daily, this would be the optimum role for you.
Location: This is a remote opportunity, but applicants must reside in the greater Seattle area.
ESSENTIAL DUTIES and RESPONSIBILITIES
Include the following. Other duties may be assigned.
Build vision and strategy. Act as a Data, BI, and AI product evangelist to build awareness and drive a step-change in how our company uses AI-driven initiatives to make decisions. Define the BI/AI-related product strategy to decrease time to insight. Identify, prioritize, and define product needs. You'll synthesize inputs from internal stakeholders, users, and competitors into prioritized roadmap investments and write product briefs to frame these for our technology teams. Oversee roadmap execution. As a Product Manager, you're the voice of our business for our technical product owners and Agile Scrum teams. Throughout the PDLC, you'll navigate prioritization trade-offs to bring the most value to our customers, workers, and business, ensuring we drive towards our strategic goals. Measure and learn. You'll determine and track product health and business metrics to test hypotheses and identify improvement opportunities. For ML and LLM features, that includes model-quality and evaluation metrics — accuracy, latency, cost, and the safeguards needed for non-deterministic systems. Collaborate and communicate. This is a highly collaborative role. You'll work closely with technical product owners and developers to define product functionality and consult and inform stakeholders from across the organization. You’ll work very closely with the other Product Managers in and outside the BI team to create and deliver on co-dependent roadmaps. Own the AI platform and APIs. Define the product strategy for the shared services, APIs, and model-delivery platform that put ML and LLM capabilities into the hands of internal teams and applications, balancing reusability, performance, and cost. Help shape a brand-new organization. You'll be on the ground floor of some exciting business improvements and will help shape our path to success. Reimagine the way people connect people to work.
EDUCATION and EXPERIENCE
3+ years of product management or similar experience with Machine Learning, Business Intelligence, and Analytics offerings, including hands-on exposure to AI/ML platforms or LLM-powered products. Academic background in product management will be considered. Experience building and delivering machine learning, business intelligence, or data analytics offerings from the ground up.
CORE KNOWLEDGE and SKILLS
Demonstrated ability to think globally and strategically and frame new and complex issues, recommend strategic choices, and focus the organization on the most critical and value-added activities. Excellent leadership skills, with a team-player attitude to drive the end-to-end solution of use cases under time pressure Strong communications skills and ability to break down complex information into relevant, digestible points for colleagues and executives. Strong analytical, problem-solving, and product management skills. Entrepreneurial self-starter excited to shape new solutions. Undergraduate degree in engineering or quantitative analysis and demonstrated experience in technical creativity, planning, and communications is valuable. An advanced degree in business administration, statistics, or similar quantitative fields is preferred. Preferred skills: Previous experience in building pricing-related solutions Previous experience in staffing or similar industry Working knowledge of common machine learning models, large language models (LLMs) and generative-AI tooling (e.g., prompt engineering, retrieval-augmented generation), and data engineering and analysis tools such as Python, Spark, data visualization, and business intelligence Working knowledge of Cloud Native database technologies such as those in the AWS product offering – Amazon Quicksight, PostgreSQL Familiarity with productizing AI platforms — APIs, shared services, MLOps/LLMOps pipelines, and the build-vs-buy tradeoffs around model hosting and vendor models
TECHNICAL KNOWLEDGE EXPECTATIONS
Ability to read and validate SQL queries and basic data models well enough to assess feasibility and translate requirements for engineering Working understanding of the ML/LLM development lifecycle — data collection, model training/fine-tuning, evaluation, deployment, and monitoring Familiarity with API design principles and RESTful/GraphQL services sufficient to scope platform and integration requirements Working knowledge of data architecture concepts, including data warehousing, ETL/ELT pipelines, and data governance practices Comfort evaluating technical trade-offs (build vs. buy, latency vs. cost, accuracy vs. interpretability) in partnership with business, engineering, and data science Ability to review technical documentation, architecture diagrams, and API specifications directly, without requiring translation from engineering
PREFERRED CERTIFICATIONS
AWS Certified Machine Learning – Specialty, AWS Certified Data Analytics – Specialty, or an equivalent cloud/ML certification Certified Scrum Product Owner (CSPO) or a comparable Agile/Scrum product certification Product management certification from a recognized program (e.g., Pragmatic Institute, Product School, AIPMM)
SUPERVISORY RESPONSIBILITIES
This position will not have any direct supervisory responsibilities.
Salary Range: $122,400 - $153,000 annually, depending on experience and geographic location. Please note that actual compensation offered may vary based on local pay requirements, and will meet or exceed state-specific minimum wage or salary thresholds.
Benefits and Well-Being:
We offer a competitive benefits package, including 6 paid holidays, 1 paid floating holiday and up to 20 days of Paid Time Off per year, Medical/Dental/Vision insurance, Company-matching 401(k) and Employee Stock Purchase Program, in addition to other programs and perks. More details about our benefits can be found here .
We consider qualified applicants with arrest and conviction records in accordance with applicable law.
You must be work authorized in the United States on a full-time basis without the need for employer sponsorship now or in the future. The Company cannot offer employment to F-1 (student) visa holders who require employer sponsorship in the future or cannot work now on a full-time basis.
TrueBlue, Inc. and its brands welcome and encourage applications from candidates with disabilities. Accommodations are available upon request for candidates taking part in the application or interview process. If you require disability-related accommodation during the application or interview process, please contact your Recruiter directly, Employee Relations at [email protected] , or 1-800-610-8920. TrueBlue, Inc. and its brands will consult with all applicants who request disability-related accommodation during the application or interview process to ensure that the accommodation provided takes into account the applicant’s individual accessibility needs.
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation, gender identity, or any other characteristic protected by law.
Salary Context
This $122K-$153K range is in the lower quartile for AI Product Manager roles in our dataset (median: $193K across 99 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 9,653 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At PeopleReady, 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 $220,200 based on 862 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($137K) sits 37% below the category median. Disclosed range: $122K to $153K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
PeopleReady AI Hiring
PeopleReady has 1 open AI role right now. They're hiring across AI Product Manager. Based in Seattle, WA, US. Compensation range: $153K - $153K.
Location Context
AI roles in Seattle pay a median of $226,100 across 973 tracked positions. That's 6% above the national 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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