Security Tooling Specialist, GSRS Security Systems and Technology

As a Security Tooling Specialist for the Global Security Systems and Technology (GSST) Technical Solutions team, you will design and deliver secure, scalable, and integrated solutions for ambiguous issues within Security Operations, while maintaining privacy and legal standards. You will serve as the technical bridge between elegant frontend user interfaces and dynamic backend infrastructure, strategically embedding Google’s AI and Large Language Model (LLM) technologies to accelerate automation for efficiency and effectiveness. By collaborating cross-functionally with end users, stakeholders, leadership, and peers, you will transform complex requirements into intuitive and impactful tools, utilizing metrics to demonstrate real-world performance and return on investment (ROI). You will be a technical expert and mentor who will elevate and advocate for software development best practices across the peer teams. From keeping Googlers safe and secure to managing disruptive events, the ability to anticipate, deter, detect, and act are the pillars of Google’s Global Security and Resilience Services (GSRS) team. As a member of GSRS you will help develop a culture where safety, security and resiliency are integrated into every facet of Google, including the creative process. You will help us continually identify, evaluate and monitor enterprise risks that could affect business activities and provide business leaders the information they need to make critical decisions. You'll collaborate with cross-functional teams to create innovative strategies and develop programs that drive sustainable effectiveness. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $152000 - $221000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . Architect and develop robust full-stack applications, partnering with infrastructure and security teams to seamlessly integrate new software solutions and tools with legacy systems. Deliver tools with properly built and supported data integrations for operational flows and business impact reporting purposes through tight collaboration with the data team. Implement embedded AI and Agentic solutions with focused development, testing, and validation to empower end users with greater efficiency and effectiveness. Own the technical roadmap and strategy to scale and sustain the solutions you deliver through purpose-fit vendor teams. Provide expert technical support for complex use cases, ensuring strict compliance with privacy and security standards, while advocating engineering best practices, code reviews, and technical growth across the organization. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience troubleshooting technical issues for internal/external partners or customers. Experience in Python, Go, or other modern backend languages. Experience designing, building, and maintaining data pipelines using SQL, and managing production infrastructure through compute infrastructure and server platforms. Experience developing and deploying enterprise solutions leveraging machine learning and artificial intelligence, with a focus on Large Language Models (LLMs). Preferred qualifications: Master’s degree in Business, Statistics, Mathematics, Economics, Engineering or Applied Science, or a related field. Experience managing and aligning teams across operational, engineering, product, and UX disciplines. Experience with front-end web development using Angular, TypeScript, or similar frameworks. Experience writing and reviewing production-ready code in a distributed environment. Experience developing AI agents through the Google Cloud Agent Development Kit framework. Bachelor’s degree or equivalent practical experience. 5 years of experience troubleshooting technical issues for internal/external partners or customers. Experience in Python, Go, or other modern backend languages. Experience designing, building, and maintaining data pipelines using SQL, and managing production infrastructure through compute infrastructure and server platforms. Experience developing and deploying enterprise solutions leveraging machine learning and artificial intelligence, with a focus on Large Language Models (LLMs).