AI-Driven Product Support Manager

Google; New York (NY); Sur place; USD 140 000 - 204 000; Plein temps

Résumé du poste

Google's gTech Users and Products (gUP) team seeks a Product Support Manager to own end-to-end customer journeys—driving AI self-service transformation, replacements, repairs modernization, and automated risk/refund workflows across Google Store.

You will translate complex operational pain points into technical product requirements, guide multi-quarter roadmaps with cross‑functional partners, and push for data‑driven improvements in cost of service and agent efficiency on a global scale.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in a project management or a customer-facing role.
• Experience deploying AI-powered customer experiences, self-service platforms, and workflow automation is preferred.

Responsabilités

• Drive strategy, business requirements, and end-to-end execution for platform overhauls and cross-functional integrations.
• Scale modernized commerce and post-purchase policies with robust fraud and financial controls.
• Translate complex operational pain points into technical product requirements and multi-quarter roadmaps.
• Identify and execute ROI-focused automation initiatives to reduce repeat contacts and handling costs.
• Lead pilots, market expansions, and legacy tool deprecations while ensuring operational readiness.

Connaissances

PM or customer-facing experience

Experience with ROI analytics

Formation

Bachelor’s degree or equivalent practical experience

Outils

SQL

Dashboards

A/B testing

Description du poste

Google's gTech Users and Products (gUP) team seeks a Product Support Manager to own end-to-end customer journeys—driving AI self-service transformation, replacements, repairs modernization, and automated risk/refund workflows across Google Store.

You will translate complex operational pain points into technical product requirements, guide multi-quarter roadmaps with cross‑functional partners, and push for data‑driven improvements in cost of service and agent efficiency on a global scale.