Senior Staff Software Engineer, AI-Empowered, Fraud and Abuse Security
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- 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
Minimum qualifications:
- Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, Go, C++, Java).
- 5 years of experience designing, building, and testing large-scale distributed systems or infrastructure services.
- 1 year of experience with AI/ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- Experience leading project teams, defining technical roadmaps, and setting engineering standards.
- Experience in designing and evaluating AI-assisted tools or automation workflows.
Preferred qualifications:
- Experience in anti-abuse, ad fraud detection, cybersecurity, or managing traffic quality systems.
- Experience designing, optimizing, or evaluating Generative AI solutions, LLM-based applications, or multi-agent orchestration systems.
- Experience building and deploying large-scale machine learning systems for fraud and abuse or security applications (e.g., fraud prevention or intrusion detection).
- Advanced proficiency in the security assessment and design of global-scale distributed systems, with experience implementing end-to-end security controls (e.g., secure SDLC, automated vulnerability discovery, or threat analysis).
- Familiarity with Google's security products, services, and underlying infrastructure.
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
The mission of Google Cloud Platform (GCP) Cyber Defense Center is to deliver unified security incident, vulnerability, and cloud-abuse management across the Cloud stack.
In this role, you will architect for GCPs Fraud and Abuse detection and mitigation platforms. You will manage ambiguous, large-scale systems problems at the intersection of security and ML, defining the technical direction for multiple teams. You will design and optimize AI-enabled defense solutions, establish security standards for AI infrastructure, and leverage data to drive critical architectural decisions. You will be a key partner to engineering leadership, guiding the technical roadmap and mentoring the next generation of AI and security experts.
US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Architect and scale robust, secure platforms that automate security checks across Google Cloud’s developer pipeline and production systems.
- Design, optimize, and evaluate AI-driven security capabilities, leading the identification of AI opportunities across fraud and abuse engineering including direct coding and model architecture.
- Establish engineering and security standards for large-scale distributed systems, ensuring robust end-to-end security.
- Analyze and distill complex technical and security data to drive key organizational decisions and roadmap prioritization.
- Provide technical leadership for multiple teams, vet system designs, and mentor executive engineers to help them grow into technical leaders in AI and security.
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