Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience leading technical projects and providing technical leadership to cross-functional teams.
• Experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• Experience in highly scalable and available distributed systems, cloud services or data platforms.
• Experience with Generative AI, Agentic AI, and Large Language Models (LLMs).
• Experience with major cloud platforms (e.g.,
  Google Cloud Platform (GCP)).
• Experience in the security domain.

About the job

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.

The Defense and Consulting team within Google Cloud Security is on a relentless mission to make organizations secure against cyber threats, confident in their readiness, and know they are never alone. Our team is passionate about giving the defender's advantage to find evil in the most advanced attacks, being incredibly efficient in their work, and leveraging best in class technologies and threat intelligence. We are at the forefront of the Agentic SOC outlook, revolutionizing how organizations defend against emerging threats, accelerating customer time-to-value, and optimizing security workflows. If you are obsessed with helping organizations become more secure, enabling security analysts and threat hunters to do their work in the best way possible, and are excited about building and introducing new technologies - this can be the role for you.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities

• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
• Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.
• Establish strategic partnerships with stakeholders to define a long-term product outlook and technology roadmap.
• Lead the integration of AI into both product solutions and engineering practices, helping to accelerate AI velocity throughout the organization.