Product Manager, Email Content AI

LinkedIn•Mountain View, CA

3h•Hybrid

About The Position

This role will be based in Mountain View or San Francisco, CA. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. We’re looking for an experienced Product Manager to lead Email Content AI at LinkedIn. This role will own the vision, strategy, and execution for how AI powers the content, personalization, and effectiveness of LinkedIn’s email retention ecosystem at a global scale. Emails are one of LinkedIn’s most important and far-reaching surfaces, helping millions of members achieve their JTBD on LinkedIn. In this high-impact role, you’ll define how AI helps deliver the right content to the right member at the right time; driving engagement, relevance, and long-term member value. You’ll operate as a full-stack product builder, owning everything from problem definition and roadmap through execution, launch, and iteration. You’ll work closely with engineering, data science, design, and cross-functional partners to build AI-powered systems that improve content selection, generation, ranking, and evaluation. You’ll also partner deeply with Marketing, Editorial, PMM, Legal, and Privacy teams to ensure solutions are effective, responsible, and aligned with LinkedIn’s values. This role plays a key part in LinkedIn’s Daily Active User growth and in its mission to create economic opportunity for every professional around the world; by helping members get more value from every email we send. Searching for your dream job? At LinkedIn, we strive to help our employees find passion and purpose. Join us in changing the way the world works.

Requirements

BS/BA Degree in a technology related field OR equivalent experience
2+ years of experience in product management or equivalent role

Nice To Haves

3+ years of experience in product management or equivalent role
Experience building or shipping AI/ML-powered products, particularly in personalization, content systems, or recommendation surfaces.
Strong understanding of experimentation, metrics, and data-driven decision making at scale.
Experience working with highly cross-functional teams across engineering, data science, design, and business stakeholders.
Ability to translate complex technical concepts into clear product direction for technical and non-technical audiences.
Experience operating in high-visibility, high-impact product areas.
Familiarity with consumer engagement, lifecycle communication, or growth surfaces is a plus.
MBA or advanced degree is a plus.

Responsibilities

Own the product vision, strategy, and roadmap for AI-powered email content across LinkedIn’s global email ecosystem.
Partner with engineering, data science, and design to define and ship scalable AI solutions, including personalization, content selection, generation, and experimentation frameworks.
Build a deep understanding of member needs, lifecycle moments, and engagement signals through qualitative research, experimentation, and data analysis.
Define clear problem statements, user stories, MVP scopes, and success metrics; measure and optimize impact against core business KPIs.
Serve as the primary POC and subject matter expert for Email Content AI, collaborating across PM, PMM, Editorial, Marketing, Legal, Privacy, and Comms teams.
Lead go-to-market planning for new AI-driven capabilities, ensuring clarity, alignment, and strong internal adoption.
Communicate and evangelize product vision, strategy, and progress to stakeholders ranging from senior leadership to execution teams.
Identify and prioritize technical investments required to support high-quality, responsible, and scalable AI systems.
Develop and track OKRs for key initiatives, ensuring alignment with broader Growth and company objectives.
Stay informed on advances in AI/ML, personalization, and content systems, translating emerging capabilities into practical product opportunities.