Full-Time Senior Principal Product Manager, Conversational Search

This high-leverage, business-critical role is an opportunity to shape how search is employed to power richer, more intuitive conversational experiences.

As the line between search and conversation blurs, you'll guide the development of our foundational search capabilities to create conversational experiences that are personalized, relevant, and grounded in trusted information.

What you get to do in this role:

• Drive product strategy for AI search, retrieval augmented generation (RAG), and question-answering capabilities that sets us up for success as we look to grow to $20B+ in revenue.
• Identify compelling product priorities and build consensus around them.
• Facilitate cross-functional teams that comprise ML research, engineering, user experience research, and design partners to bring high-quality products to life.
• Manage the end-to-end product lifecycle and assume ownership of outcomes.
• Integrate user research, customer pilots, and market analysis into product requirements to enhance user and customer satisfaction.
• Translate complex problems into clear and compelling requirements.
• Develop multimodal communications that speak to diverse audiences, both internal and external, and technical and non-technical.
• Forge partnerships with other product teams to drive adoption of search and GenAI capabilities.
• Establish and refine metrics and framework for measuring the quality and value of search and GenAI.
• Serve as team guide and coach lower-level employees.

To be successful in this role, you have:

1. 12+ years of related product management experience.
2. Direct experience building GenAI, natural language processing, or search capabilities.
3. Strong prioritization skills and the discipline to focus on high-impact activities.
4. Experience capturing and defining product requirements and transforming them into a roadmap.
5. Deep customer empathy and a track record delivering customer-centric solutions.
6. Expertise in synthesizing qualitative and quantitative data to validate hypotheses, measure success, and inform product direction.
7. Experience navigating ambiguity, identifying underlying problems, and clearly articulating tradeoffs around potential solutions.
8. Demonstrated ability to navigate and solve problems at the intersection of machine learning quality and UX design.

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