Principal Product Manager, Core AI Platform

Qualtrics Qualtrics · Seattle · Seattle, WA · Product - AI

Principal Product Manager for Qualtrics' Core AI Platform, responsible for defining the strategy and roadmap for foundational AI capabilities including agent infrastructure, evaluation, observability, and safety. This role bridges the needs of enterprise customers and internal AI product builders, focusing on creating scalable, trusted, and differentiated AI experiences.

What you'd actually do

  1. Define the future of the core AI infrastructure that powers intelligent experiences across Qualtrics.
  2. Build the platform capabilities that enable product teams to create trusted, scalable, and differentiated AI experiences using structured and unstructured experience data.
  3. Own the product strategy for foundational AI capabilities such as ontologies and semantic systems, agent infrastructure, context and memory, tools and orchestration, agent evaluation, observability, and AI safety.
  4. Manage the entire lifecycle for multiple functional areas of the Core AI Platform, 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.

Skills

Required

  • Product strategy development
  • Roadmap definition
  • Cross-functional collaboration (product, engineering, data science, research, design)
  • Understanding of enterprise customer needs
  • Understanding of internal AI product builder needs
  • Prioritization based on customer value, developer productivity, technical leverage, reuse, and differentiation
  • Making product and architectural tradeoffs
  • Defining evaluation frameworks for AI quality, reliability, and safety
  • Developing shared platform capabilities
  • Communicating vision and roadmap to senior leaders and stakeholders
  • Defining and monitoring KPIs for platform adoption, AI quality, developer velocity, reliability, and customer impact
  • Staying abreast of AI developments (agents, foundation models, evaluation, context engineering, semantic systems, enterprise AI infrastructure)
  • Translating AI technologies into product opportunities

Nice to have

  • Experience with ontologies and semantic systems
  • Experience with agent infrastructure, orchestration, planning, tool use, delegation, and multi-agent patterns
  • Experience with agent evaluation systems (offline and online)
  • Experience with context engineering and memory systems
  • Experience with AI observability and debugging
  • Experience with model infrastructure and abstraction layers
  • Experience with guardrails, permissions, governance, and safety systems for enterprise AI

What the JD emphasized

  • agent infrastructure
  • agent evaluation
  • observability
  • AI safety
  • trusted
  • scalable
  • differentiated AI experiences
  • enterprise customers
  • internal AI product builders
  • agent runtimes and orchestration
  • tool use
  • context engineering
  • memory
  • model access
  • guardrails
  • governance
  • security
  • reliability
  • explainable
  • reliable AI systems

Other signals

  • Define the future of the core AI infrastructure that powers intelligent experiences across Qualtrics.
  • Build the platform capabilities that enable product teams to create trusted, scalable, and differentiated AI experiences using structured and unstructured experience data.
  • Own the product strategy for foundational AI capabilities such as ontologies and semantic systems, agent infrastructure, context and memory, tools and orchestration, agent evaluation, observability, and AI safety.