About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Globally, online payment fraud is expanding at an alarming rate and has become the primary threat we face. As Google's business grows and we enter new markets, the pressure to protect our platform from these sophisticated attacks intensifies. Trust and safety are critical for every product, and our team provides the essential payment fraud protection for a wide range of Google businesses from Cloud and YouTube to the Google Store and more.

In this role, you will build customizable and extensible fraud protection services. You will build Artificial Intelligence (AI)-driven risk management solutions, bringing to bear all the advances with the rich data set and signals we have in payments and across Google!
Whether it is paying online with Autofill, using tap and pay in stores, or using the Google Pay app, the Payments team at Google is focused on making payments simple, seamless, and secure. In addition to consumer payment technologies, the Payments team also powers the money movement between Google and its consumers and businesses.

The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Internalize fraud and abuse patterns across businesses.

• Create novel solutions leveraging advances in Generative Artificial Intelligence (GenAI) and Machine Learning (ML), rich data stats, and fraud analyses.

• Internalize needs across businesses and propose general solutions shared across domains.

• Develop a Machine Learning (ML)-driven Risk Management solution in delivering step reduction in losses, customer insults, and complexity, and step increase in speed at which we can catch and nip fraud.

• Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 2 years of experience with software development in Python and Java, or 1 year of experience with an advanced degree.

• 1 year of experience developing algorithms for intelligent agents, including areas such as planning, reinforcement learning, or multi-agent systems.

• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

• 1 year of experience in big data and analytics.

• Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision ).

Preferred qualifications

• Master's degree or PhD in Computer Science or a related technical fields.

• 2 years of experience with data structures and algorithms.

• Experience optimizing, deploying, developing or operating global payment solutions.

• Experience developing accessible technologies.

• Experience in the electronic payments industry or related area including card, direct debit, online banking and other methods of payment.

• Ability to start in Mountain View in May 2026.