Senior Staff Software Engineer, AI-Empowered, Fraud and Abuse Security

Job description

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. 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.