Product Manager, AdSpam Conversion and Bidding Integrity, Google Ads

Ad fraud is one of the biggest challenges facing the digital advertising industry across web, app, video, and beyond. AdSpam’s mission is to protect advertisers, users, publishers, and Google from fraud and abuse. We prevent the exploitation of Google’s ad systems for monetary gain, collaborate across the industry to combat fraud beyond Google, and safeguard business against sophisticated, persistent, and globally distributed threats to ensure the long-term health of a free and open digital ecosystem.

Google’s advertising business increasingly relies on automated campaign strategies powered by AI bidding and optimization models. These systems automatically place ads to drive real business results—such as purchases, app installs, and leads (conversions). However, their effectiveness depends entirely on the integrity of their training data. When fraudsters manipulate conversion signals or generate fake activity, these models can be tricked into directing advertiser spend toward fraudulent or low-value inventory.

The Conversions and Bidding Integrity team directly addresses this challenge. As a Product Manager, you will protect the critical signals feeding Google’s business generation and bidding models from advanced abuse, complementing broader Invalid Traffic (IVT) defenses to steer advertiser budgets away from risk and toward genuine business value.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Identify emerging fraud vectors and design product strategies to protect automated bidding algorithms and conversion measurement from manipulation.
• Partner closely with engineering teams to integrate robust fraud-prevention mechanisms directly into Google’s core ad-placement models.
• Collaborate across Ads Privacy and Safety, Trust and Safety, and Product leadership to define technical requirements and establish safety standards.
• Lead the rollout of sustainable anti-fraud protections across Machine Learning (ML) models and high-volume ad spend pipelines.
• Safeguard advertiser trust, protect business for legitimate publishers, and maintain the integrity of the broader advertising ecosystem.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 3 years of experience in product management or related technical role.
  
• 1 year of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc.).
• Experience integrating generative AI tools or LLM interfaces into workflows.
• Experience with digital advertising technologies.
• Experience in product management or technical strategy focused on trust and safety, anti-abuse, or fraud prevention.

Preferred qualifications:

• Master's degree in a technology or business related field.
  
• 2 years of experience in a business function or role (e.g., strategic marketing, business operations, consulting).
  
• 2 years of experience in a role preparing and delivering technical presentations to senior leadership.
  
• 2 years of experience working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders.
  
• 1 year of experience in software development or engineering.
  
• Ability to protect the ads ecosystem and user experience.