Sr. Product Manager, Enterprise AI

TrueBlue•Seattle, WA

3d•Remote

About The Position

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. This is a remote opportunity, but applicants must reside in the greater Seattle area.

Requirements

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.
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.
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

Nice To Haves

An advanced degree in business administration, statistics, or similar quantitative fields is preferred.
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
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)

Responsibilities

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.
Oversee roadmap execution.
Measure and learn.
Collaborate and communicate.
Own the AI platform and APIs.
Help shape a brand-new organization.
Reimagine the way people connect people to work.