AI/ML Data Analytics Program Manager - Search

Google; New York (NY); On-site; USD 159,000 - 230,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

Google is seeking a Program Manager for the Search team in the United States who will lead complex, cross-disciplinary projects from inception to delivery, coordinating stakeholders, schedules, risks, and communications across multiple offices.

You will improve user experience by analyzing feedback, guiding end-to-end programs, and partnering with Ops to build scalable automation, with emphasis on generative AI integrations and LLM interfaces.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in program or project management.
• Experience in data analysis.
• Experience in Generative AI.
• Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.

Responsibilities

• Define and lead the overarching program strategy for Search user feedback. Translate ambiguous feedback data into clear, measurable objectives, driving the end-to-end program lifecycle from pre-launch to post-launch environments.
• Architect and run a centralized product health ecosystem that provides a single, actionable view of user feedback signals for feature teams and leadership. Use this view to drive consistent improvements across First-Party (1P) and pre-launch features.
• Partner closely with Operations to build scalable automation including anomaly detection and alert logic to ensure rapid triage, routing, and resolution of emerging issues.

Skills

Program management

Data analysis

Generative AI

LLM integration

Cross-functional collaboration

Education

Bachelor's degree or equivalent practical experience

Job description

Google is seeking a Program Manager for the Search team in the United States who will lead complex, cross-disciplinary projects from inception to delivery, coordinating stakeholders, schedules, risks, and communications across multiple offices.

You will improve user experience by analyzing feedback, guiding end-to-end programs, and partnering with Ops to build scalable automation, with emphasis on generative AI integrations and LLM interfaces.