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Qualtrics is seeking a Senior Product Manager to own the product strategy and lifecycle for the Understand layer—the intelligence engine that transforms raw experience data into structured meaning, prediction, and insight across the entire platform.
In this role, you will define the future of Qualtrics' AI capabilities, owning product strategy for semantic systems, text analytics enrichments, predictive modeling, simulation, and benchmarking. You'll also own the Core AI platform foundations including agent infrastructure, context and memory management, tools and orchestration, agent evaluation, observability, and AI safety.
You will manage the complete product lifecycle across multiple functional areas: framing problems, aligning on architecture and direction, forming implementation plans, delivering features, and iterating until capabilities are world-class.
Key responsibilities include partnering with product, engineering, data science, research, and design teams to understand their needs for enrichment and modeling capabilities. You'll develop deep expertise in both enterprise customer requirements and internal AI product builder needs, translating these into strategy, requirements, and roadmaps.
You will prioritize investments based on customer value, insight quality, developer productivity, technical leverage, and competitive differentiation. You'll collaborate with engineering and AI research teams to make thoughtful product and architectural tradeoffs in a rapidly evolving landscape.
You'll develop frameworks for evaluating quality, accuracy, reliability, safety, and business impact of enrichment models and agentic AI systems. You'll build benchmarking discipline to prove Qualtrics' models outperform alternatives internally and to customers.
You'll create shared capabilities that accelerate AI development across Qualtrics while providing enterprise-grade reliability, governance, security, and observability. You'll communicate compelling vision and roadmaps to senior leaders, product teams, technical stakeholders, and customers.
Finally, you'll define and monitor KPIs for adoption, model quality, prediction accuracy, evaluation performance, developer velocity, reliability, and customer impact. You'll stay at the forefront of foundation models, agents, evaluation methods, semantic systems, causal modeling, simulation, and enterprise AI infrastructure, translating developments into concrete product opportunities.
