Principal Scientist, Cloud AI Research

Principal Scientist As Principal Scientist, you will serve as the recognized technical leader within our strategic research areas. You will be responsible for driving our current and future research roadmap with regard to agentic AI platforms and design. You will have the autonomy to decide how to prioritize research into agentic platforms, maintaining a portfolio of research projects that are driven by product innovation, fundamental research, and infrastructure goals. In this role, you will lead large-scale efforts by identifying future work, questioning traditional lines of thought, and synthesizing assets from various research areas to drive Google in new product or technology directions. By bridging the gap between advanced research and product development, you will help unlock high-impact vertical agents—such as AI planners, forecasters, and engineers—and horizontal agents that scale enterprise efficiency. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Follow research trends in agentic AI to determine the group's research and innovation strategy. Drive research to overcome challenges like context-rot and massive token costs in complex, multi-day agent tasks. Work closely with all Infrastructure teams, Research/GDM teams, and customers to improve adoption. You will partner most closely with Google Deepmind and Vertex AI, our customer-facing agent platform for Google Cloud. Lead the development of high-impact vertical agents (e.g., forecasting, planning, and design agents) and horizontal agents designed to accelerate both research and product development velocity. Help lead a small, senior research team by providing technical direction, management, and mentorship. Draw other top research talent to Google and Google Cloud. In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Seattle, WA, USA. Minimum qualifications: PhD in Computer Science, a related field, or equivalent practical experience. 15 years of experience with research agendas across multiple teams or projects. Experience in agentic AI systems and platforms. Authored and co-authored multiple publications in systems research venues. Preferred qualifications: 20 years of research and engineering experience, with a PhD in Electrical Engineering, Computer Science, or related field. Multidisciplinary experience leading both product and engineering or research/applied science Ability to quickly ramp up in new subject areas with short notice to guide mission-critical research into the largest potential risks related to Google infrastructure usage. Credibility within the AI research community, with the ability to influence external thought leaders and help advocate for Google. Communication and leadership skills needed to influence technical leaders across the company. CompliancePoint