Sr. Product Manager, Enterprise AI
Get alerts for roles like this
More Sr. Product Manager, Enterprise AI roles in United States — straight to your inbox. No account needed.
Applying to this role? Tailor your résumé to this job description in one click, then download it clean — no watermark, no subscription.
Job Description
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: Remote 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