Senior Product Manager, AI Evaluation & Quality| Level 18| US: Remote

Let's be unstoppable together!

Circana is a leading provider of technology, AI, and data solutions for consumer packaged goods companies, manufacturers, and retailers. Our predictive analytics and Liquid Data® platform help clients measure market share, uncover consumer behavior, and drive growth-powered by six decades of expertise and an expansive, high-quality data set.

At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives. We're a global company dedicated to fostering inclusivity and belonging. We value and celebrate the unique experiences, cultures, and viewpoints that each individual brings. By embracing a wide range of backgrounds, skills, expertise, and beyond, we create a stronger, more innovative environment for our employees, clients, and communities. With us, you can always bring your full self to work. Join our inclusive, committed team to be a challenger, own outcomes, and stay curious together. Circana is proud to be Certified™ by Great Place To Work®. This prestigious award is based entirely on what current employees say about their experience working at Circana. Learn more at www.circana.com.

Role Overview

The Liquid AI Evals role will build and own the evaluation framework used to validate the quality, reliability, safety, and business value of Circana's AI agents. Reporting into the Liquid AI Product Leader, this role will establish repeatable testing practices that let the team move quickly while ensuring new agent capabilities meet client, business, and technical expectations before and after launch.

Job Responsibilities

• Define evaluation strategies, methodologies, metrics, and acceptance thresholds for Circana's AI agents. • Build evaluation frameworks for AI agent and agentic workflow capabilities. • Partner with the Liquid AI Product Leader, engineering, and each product vertical to validate agent performance before release. • Develop representative test scenarios, golden datasets, benchmarks, and scoring approaches, including LLM-as-a-judge methods where appropriate. • Evaluate agent quality, accuracy, consistency, reliability, safety, and client value. • Identify failure patterns and translate findings into product improvement recommendations. • Establish ongoing monitoring of production traces to detect performance changes following launch. • Document evaluation results and communicate findings to technical and business audiences. • Promote consistent evaluation standards as Liquid AI's capabilities expand across product verticals.