Field Solutions Architect III, Generative AI, Google Public Sector

As a Field Solutions Architect, you will support the Rapid Innovation team in Google Public Sector. You will construct rapid prototype generative AI applications tailored to public sector customers.

You will leverage generative AI technologies to develop innovative solutions and validate their efficacy. You will swiftly showcase the latest generative AI capabilities through direct collaboration with customers.

In this role, you will closely collaborate with our Product team to eliminate obstacles and shape the future trajectory of our offerings. In addition, you will disseminate the lessons learned to customers and internal Google teams.

Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $183000 - $266000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Minimum qualifications:

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
  
• 8 years of experience in Python or other programming languages in machine learning (e.g., Java, C++, Go).
• Experience in applied AI, with a focus on designing and evaluating systems around foundation models (e.g., prompt engineering, fine-tuning, RAG, orchestrating model interactions with external tools to deliver solutions).
• Experience architecting, deploying, or managing solutions on a cloud platform.
• Active, or the ability to obtain, Top Secret/SCI security clearance.

Preferred qualifications:

• Master's degree in Computer Science, Engineering, or a related technical field.
• Experience with distributed training and optimizing performance versus costs.
• Experience supporting or selling to U.S. federal customers.
• Experience in system design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.
• Experience training and fine tuning models in environments (e.g., image, language, recommendation) with accelerators.
• Ability to demonstrate a bias for action and apply product insights to solve immediate customer issues and unlock long-term value.