About this role
As the Product Manager for the Chemical, Biological, Radiological, Nuclear and Conventional Explosives team (CBRNE), you will sit at the intersection of frontier artificial intelligence, domain science, and AI safety efforts. In this role, you will partner with scientific subject-matter experts (SMEs), engineers, program managers, and wider stakeholders to develop our approach to CBRNE topics. You will be responsible for defining the product goal, strategy, and execution roadmap for tools and infrastructure that safeguard Gemini and next-generation models against high-stakes risks in close collaboration with the Head of CBRNE and the leadership team. You will drive initiatives such as end-to-end data security frameworks, support the automation of advanced red-teaming and evaluation pipelines, and manage cross-product area partnerships on behalf of the effort.Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google (https://www.google.com/about/careers/applications/benefits/).
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in product management or related technical strategy roles, including taking technical products, platforms, or safety frameworks from conception to launch.
- Experience working with large language models (LLMs), generative AI agents, and related safety evaluation or mitigation systems.
Preferred qualifications:
- Experience within a frontier AI lab, national laboratory, government defense or intelligence organization, bio-security institute, or specialized scientific research institution.
- Experience partnering with safety experts, policy teams, and enterprise stakeholders to translate technical safety capabilities into safety mitigations, benchmarks, and deployment playbooks.
- Define key goals and priorities within the effort across different workstreams, in partnership with subject matter experts, engineering, and program management.
- Curate and be responsible for effort-wide success metrics, while proactively identifying high-value new impact opportunities for the effort.
- Deliver specific projects within the portfolio, including advancing the effort’s data security strategy.
- Develop relationships with key partner stakeholders within Alphabet, including executives, in order to enable collaboration across product areas.
- Gather feedback for the effort and partner with our teams to action and improve our work in this domain.