Software Engineer III, Agentic AI Systems, Cloud Security

Write product or system development code. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.Develop and launch of next-generation Agentic features for Google SecOps. Develop foundational AI platform to support and accelerate security sgents development.Scale the product and defend the enterprises from emerging threatsMinimum qualifications:Bachelor’s degree or equivalent practical experience.2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).Experience with state of the art 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, Artificial Intelligence, or a related field.2 years of experience with data structures and algorithms.Experience in security domains.Experience in highly scalable and available distributed systems, cloud services or data platforms.Proven experience in building and deploying Agentic AI systems.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.As an AI Engineer, you will contribute to the research, design, development, and operational excellence of the Agentic Platform and Capabilities for Google SecOps. This role is critical for turbocharging and enabling autonomous agentic SOC for the next wave of AI-driven cybersecurity solutions. You will build AI platforms, systems and sgents that can reason, investigate, and defend against 22-second attacks.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefitsLearn more about benefits at Google.In most instances, this position requires in-person interviews as part of the hiring process.Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Bachelor’s degree or equivalent practical experience.2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).Experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).