Senior Product Manager

At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. We are the creators and stewards of the Experience Management category serving over 18K clients globally.

• Define the future of Qualtrics' Understand layer — the intelligence that turns raw experience data into structured meaning, prediction, and insight across the entire portfolio.
• Own the product strategy for the capabilities that let AI systems and product teams reason about experience data: ontologies and semantic systems, text analytics enrichments, prediction, simulation, and benchmarking.
• Own the Core AI platform foundations that these capabilities depend on: agent infrastructure, context and memory, tools and orchestration, agent evaluation, observability, and AI safety.
• Manage the entire lifecycle for multiple functional areas of Understand, from framing the problem, to aligning on architecture and product direction, to forming the plan, delivering implementation, and iterating until the capabilities are world-class.

• Partner with product, engineering, data science, research, and design teams across Qualtrics to understand what enrichment, modeling, and platform capabilities they need to build exceptional AI products.
• Develop a deep understanding of the needs of both enterprise customers and internal AI product builders, and translate those needs into strategy, requirements, and roadmaps.
• Define product strategy across the Understand surface area: ontologies and semantic layers, text analytics and enrichment pipelines, predictive models, simulation, benchmarking, and the agent runtime, orchestration, memory, evaluation, and guardrail capabilities that support them.
• Prioritize investments based on customer value, insight quality, developer productivity, technical leverage, reuse across Qualtrics products, and opportunities for competitive differentiation.
• Collaborate deeply with engineering, AI research, and data science teams to make thoughtful product and architectural tradeoffs in a rapidly evolving technical landscape.
• Develop clear frameworks for evaluating the quality, accuracy, reliability, safety, and business impact of enrichment models, predictive systems, and agentic AI.
• Build the benchmarking discipline that lets Qualtrics prove its models and enrichments are better than alternatives — internally and to customers.
• Create shared capabilities that accelerate AI development across Qualtrics while providing the reliability, governance, security, and observability required by enterprise customers.
• Develop and communicate a compelling vision and roadmap to senior leaders, product teams, technical stakeholders, and customers.
• Define and monitor meaningful KPIs for adoption, model and enrichment quality, prediction accuracy, evaluation performance, developer velocity, reliability, and customer impact.
• Stay at the forefront of developments in foundation models, agents, evaluation methods, semantic systems, causal and predictive modeling, simulation, and enterprise AI infrastructure — and translate them into concrete product opportunities.