Product Manager II - AI-Driven Search & Recommendations

Google; New York (NY); On-site; USD 163,000 - 236,000; Full time

Job summary

Google is seeking a Product Manager to guide cross‑functional teams from concept to launch, connecting technical and business worlds. You will break down complex problems, define roadmaps, and shape product narratives that deliver measurable impact for users.

The role emphasizes AI‑driven search, recommendation systems, and UX improvements, with collaboration across Marketing, Data Science, and User Research.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in product management or a related technical role.
• 2 years of experience taking technical products from conception to launch.
• 1 year of experience with recommendation systems, ranking systems or search quality.
• Experience integrating generative AI tools or Large Language Model interfaces into workflows.

Responsibilities

• Define product roadmaps by operationalizing strategy.
• Develop and secure buy‑in for a product vision that identifies, defines, and supports the overall product narrative and direction, achieving an outcome that is greater than the sum of its parts.
• Validate the market size and opportunity (e.g., user‑based, strategic opportunity, revenue).
• Organize video information to make it universally accessible and useful for users looking to learn and be entertained.
• Shape how users find answers and discover content by solving problems using AI.

Skills

Product management

Recommendation systems

Search quality

AI integration

Cross-functional collaboration

Education

Bachelor's degree

Job description

Google is seeking a Product Manager to guide cross‑functional teams from concept to launch, connecting technical and business worlds. You will break down complex problems, define roadmaps, and shape product narratives that deliver measurable impact for users.

The role emphasizes AI‑driven search, recommendation systems, and UX improvements, with collaboration across Marketing, Data Science, and User Research.