Senior Product Manager - Core AI (Understand)

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. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.

When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.

Senior Product Manager, Core AI (Understand)

Why We Have This Role

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.

How You'll Find Success

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.

How You'll Grow

By shaping the technical and product foundations for how Qualtrics understands experience data.

Through developing deep expertise across ontologies, semantic systems, text analytics, prediction, simulation, benchmarking, agent architecture, and evaluation.

By making high-leverage product decisions that influence multiple product lines and teams.

Through leading complex, ambiguous initiatives that require alignment across product, engineering, research, data science, security, and go-to-market organizations.

By developing your ability to connect rapidly evolving AI technologies to durable customer value and differentiated product strategy.

Things You'll Do

Develop and execute the product strategy for Qualtrics' Understand layer.

Define the foundational architecture and capabilities required for teams across Qualtrics to build reliable, differentiated AI experiences.

Lead product strategy for areas including:

Ontologies and semantic layers — grounding AI systems in the meaning and relationships within enterprise experience data.

Text analytics and enrichments — topic and theme detection, sentiment and emotion, intent, effort, entity extraction, summarization, and the enrichment pipelines that make unstructured feedback machine-usable at scale.

Prediction — predictive models over experience and operational data, including churn, satisfaction, and outcome modeling, and the drivers behind them.

Simulation — modeling how experience programs, interventions, and design choices would perform before they ship, including synthetic respondents and scenario modeling.

Benchmarking — internal and external benchmarks for model and enrichment quality, plus customer-facing benchmarks that put results in competitive and industry context.

Agent infrastructure — orchestration, planning, tool use, delegation, and multi-agent patterns.

Agent and model evaluation — offline and online evaluation systems, task success measurement, quality frameworks, regression testing, and human-in-the-loop evaluation.

Context engineering, memory, and retrieval — mechanisms for providing agents with the right information at the right time.

AI observability and debugging — capabilities that help teams understand why AI systems behave the way they do.

Model infrastructure and abstraction layers — letting Qualtrics teams use the right models for the right tasks while managing cost, latency, reliability, and quality.

Guardrails, permissions, governance, and safety — the systems required for trusted enterprise AI.

Work closely with product teams across Qualtrics to understand their AI use cases and identify opportunities for shared capabilities.

Connect with enterprise customers to understand their expectations for accurate, explainable, governed, and reliable AI systems.

Discover and prioritize requirements from product teams, customers, prospects, analysts, researchers, engineers, and the broader AI ecosystem.

Write Product Investment Documents and turn strategy into clear investment decisions, roadmaps, and measurable outcomes.

Manage complex cross-functional work across product, engineering, AI research, data science, UX design, and research.

Create strong adoption strategies so that new capabilities are easy to discover, easy to use, and meaningfully improve the speed and quality of AI product development.

Know the technical landscape, adoption metrics, model quality measures, and emerging market trends better than anyone.

Lead the rollout of new capabilities, including internal adoption, developer enablement, documentation, customer communication, and external positioning where appropriate.

What We're Looking For On Your Resume

Bachelor's degree in Engineering, Computer Science, Data Science, Business, or a related field.

5+ years of product management experience,