Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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
- Drive the technical direction and execution for all machine learning (ML) and AI initiatives within the team, acting as the central tech lead for our Generative AI transformation.
- Design, build, and scale the core infrastructure and pipelines necessary to develop, fine-tune, and deploy autonomous security agents (like our alert response agents) into production.
- Create testing and evaluation methodologies to continuously measure the safety, accuracy, and performance of Large Language Models (LLMs) and agentic workflows in high-stakes security environments.
- Partner closely with software engineering, product, and UX teams to seamlessly blend deterministic playbooks with dynamic AI intelligence, ensuring a flawless experience for SOC analysts.
- Mentor peers, set the standard for ML operational excellence, and foster a startup-like culture of rapid, safe experimentation and innovation.
Qualifications
Minimum qualifications:
- Batchelor's degree or equivalent practical experience.
- 10 years of experience in software engineering and data science.
Preferred qualifications:
- Experience leading the technical direction of machine learning or data science projects from inception to production.
- Experience developing, fine-tuning, and deploying generative AI and Large Language Models (LLMs) in enterprise environments.
- Experience designing and implementing evaluation frameworks to measure the safety, accuracy, and performance of AI models.
- Experience architecting machine learning infrastructure and data pipelines for autonomous or agent-based systems.
- Experience collaborating with cross-functional software engineering, product management, and UX teams to integrate AI models into user-facing products.
- Experience working with cybersecurity concepts, such as incident response, threat detection, SIEM, or SOAR workflows.