Launch Manager, Google Play Trust and Safety

Launch Manager, Google Play Trust and Safety Corporate FARE: Google Location: Kirkland, WA, USA; Austin, TX, USA Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Austin, TX, USA . Minimum qualifications: Bachelor's degree or equivalent practical experience. 4 years of experience in data analytics, trust and safety, policy, cybersecurity, or a related field. Preferred qualifications: 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 well in a cross-functional team environment with a focus on knowledge sharing and collaboration. Excellent communication and presentation skills (written and verbal) and the ability to influence cross-functionally at various levels. Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment. About the job Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety. 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, all the way to production deployment and post-launch monitoring. You are a resolute problem-solver and a meticulous project manager who ensures all launch requirements are met on time, while simultaneously maintaining our high standards for AI quality and operational readiness. 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 all policy and documentation requirements are fully met prior to production. Implement post-launch operational excellence and quality assurance, leading initial incident investigations for metric breaches and collaborating on policy or prompt adjustments. Oversee vendor resourcing requests to facilitate human evaluation, dataset app sampling, and ground-truth labeling for AI decision ratings. Establish ongoing maintenance and operational support pipelines, continuously refine evaluation workflows to enhance AI classifier accuracy and performance. 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