Software Engineer II, Google Threat Intelligence

Software Engineer II

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.

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.

Responsibilities:

• Design, develop, test, deploy, maintain, and improve software.
• Research, design, and implement artificial intelligence-driven solutions leveraging large language models for various security-related use cases, such as natural language understanding of threat intelligence, automated report generation, and intelligent query processing.
• Develop and deploy autonomous and semi-autonomous artificial intelligence agents capable of performing complex tasks, such as automated malware analysis, threat hunting, or incident response support.
• Evaluate and integrate large language models and agentic frameworks, considering performance, cost, and security implications.
• Contribute to the entire lifecycle of artificial intelligence-powered features, from ideation and prototyping to production deployment and monitoring.