Sr Product Manager

LexisNexis Intellectual Property (LNIP) builds patent search, data, and analytics solutions for corporations, law firms, and government agencies worldwide. In this hybrid role based in Horsham, PA, the Sr. Product Manager will own one or more product features, drive project execution, and shape product development plans while advancing AI-enabled capabilities for patent search and analytics workflows.

You will work at the intersection of data, AI, and professional workflows, helping improve search quality, relevance, and usability across critical stages of the patent lifecycle, including prior art search, patentability, and freedom to operate analysis. The role also emphasizes coordinating cross-functional efforts through launch and post-release learning, including using customer input and evidence from metrics to guide decisions.

What you will do

• Gather, evaluate, and understand customer use cases, including opportunities where AI, data, and search capabilities can improve high-stakes professional workflows.
• Create and deliver AI-enabled product features and capabilities that solve meaningful customer problems and earn customer trust.
• Define product requirements, success metrics, and evaluation approaches for AI-enabled capabilities in partnership with engineering, data, design, and customer-facing teams.
• Evaluate output quality, reliability, explainability, and user adoption for AI-enabled solutions.
• Lead and mentor team members, supporting peer development and participating in recruitment.
• Leverage and identify metrics and data to track progress against customer needs, product outcomes, and project budgets.
• Develop and communicate clear go-to-market launch plans through coordinated development with external, customer-facing teams.
• Own key end-to-end product lifecycle components, from discovery and planning through release, adoption, and post-release learning.
• Develop and communicate product vision and roadmap plans aligned with business strategy, including reusable platform opportunities, for critical stakeholders.

What you bring

• A degree in a technical field or demonstrated technical acumen and experience.
• Experience building or managing AI-enabled, data-intensive, search, or other complex enterprise products, or comparable experience applying AI or ML capabilities to customer workflows.
• Sound product judgment for AI-enabled products, including the ability to frame valuable use cases, partner with technical teams, evaluate output quality, and address user trust, explainability, and risk.
• Strong problem-solving skills and the ability to lead collaboration to resolve issues.
• The ability to interact professionally with internal and external customers.
• Experience mentoring or training others and serving as a subject matter expert.
• Excellent verbal and written communication skills, with the ability to build relationships with customers and stakeholders.
• Analytical thinking and strong organizational skills for managing multiple priorities.
• Product development knowledge, including developing related business cases, content, and product plans.
• Significant Product Management experience from collaborative conceptualization through post-release management.

Compensation and benefits

• Salary: USD 104,900 - 174,700 per year
• Healthy work/life balance
• Shared parental leave
• Study assistance
• Sabbaticals
• Annual incentive bonus

Employment conditions

• Must be a U.S. citizen to apply.
• Must successfully pass a background investigation and achieve Public Trust security clearance.
• Preference for candidates located near the Horsham, PA office for a hybrid onsite schedule.

About the team and mission

• LNIP provides patent search, data, and analytics solutions used by corporations, law firms, and government agencies worldwide.
• The Reed Tech team builds and operates the data and technology foundation behind these solutions, managing one of the world’s largest and most comprehensive patent datasets.
• The work supports workflows across the patent lifecycle, focusing on improving search quality, relevance, and usability while advancing AI-driven capabilities to reduce manual effort and increase confidence in high-stakes decisions.