Field Solutions Architect III, Generative AI, Google Public Sector

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 training and fine tuning models in environments (e.g., image, language, recommendation) with accelerators.
• Experience in system design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.
• Ability to demonstrate a bias for action and apply product insights to solve immediate customer issues and unlock long-term value.

About the job

You will leverage generative AI technologies to develop 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.

Responsibilities

• Be a trusted advisor to customers by understanding their business process and objectives. Design and build end-to-end genAI-driven solutions spanning AI, data, and infrastructure.
• Demonstrate how Google Cloud is differentiated by working with customers on application prototypes; demonstrating generative AI features; prompting and tuning models; and optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues in generative AI applications.
  
• Build repeatable technical assets such as scripts, templates, reference architectures, etc. to enable customers and internal teams. Work with peers to include the full cloud stack into overall architecture.
  
• Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements.
  
• Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement. Travel as needed.