Launch Manager, Google Play Trust and Safety

Google•Kirkland, WA

16h•$116,000 - $166,000

About The Position

As a Launch Manager within the Operations Excellence team, you will direct the successful deployment of AI app review agents across various Trust and Safety verticals. You will serve as the central partner for cross-functional coordination, guiding projects through a multi-step launch playbook—from initial prompt creation and prompt tuning through production deployment and post-launch monitoring. The role calls for a resolute problem-solver and meticulous project manager who ensures launch requirements are met on time while maintaining high standards for AI quality and operational readiness. Google Trust & Safety team members identify and address major challenges to the safety and integrity of Google's products. They work globally and cross-functionally with engineers and product managers to fight abuse and fraud and promote user safety.

Requirements

Bachelor's degree or equivalent practical experience.
4 years of experience in data analytics, trust and safety, policy, cybersecurity, or a related field.

Nice To Haves

2 years of experience in AI/ML operations.
Experience working with Large Language Models (LLMs) or prompt engineering.
Experience in content policy, anti-abuse, and reviewing online content.
Ability to work effectively in a cross-functional team environment, with a focus on knowledge sharing and collaboration.
Excellent written and verbal communication and presentation skills, with the ability to influence cross-functionally at various levels.
Excellent problem-solving and critical-thinking skills, attention to detail, and ability to work in an ever-changing environment.

Responsibilities

Drive end-to-end program management for LLM and AI classifier launches in Google Play Trust and Safety, partnering with product, engineering, policy, and operations to maintain strict timelines and align with executive OKRs.
Coordinate cross-functional launch readiness by proactively unblocking dependencies, securing steering committee approvals, and ensuring policy and documentation requirements are met before production.
Lead post-launch operational excellence and quality assurance, including initial investigations of metric breaches and collaboration on policy or prompt adjustments.
Oversee vendor resourcing requests for human evaluation, dataset app sampling, and ground-truth labeling for AI decision ratings.
Establish ongoing maintenance and operational support pipelines, and refine evaluation workflows to improve AI classifier accuracy and performance.