Google

Field Solutions Architect II, Generative AI, Google Public Sector

Google Washington, District of Columbia, United States · $152K–$221K/yr

Software Development · 10,001+ employees

7 h ago
software-architect Senior (5-10 yrs) Full-time United States
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About the role

You will design and build end-to-end generative AI solutions for public sector customers while acting as a trusted technical advisor. Additionally, you will collaborate with product teams to influence Google Cloud strategy and create repeatable technical assets to enable internal and external teams.

What they look for

Python Generative AI Machine Learning Prompt Engineering Fine-tuning Retrieval-augmented generation Cloud architecture System design Data pipelines ML pipelines Google Cloud Distributed training Benchmarking Technical advisory Prototyping

Requirements

Candidates must have a bachelor's degree in a STEM field and at least 6 years of experience in Python or similar programming languages for machine learning. You must also possess experience in applied AI, cloud platform management, and the ability to obtain a Top Secret/SCI security clearance.

Benefits

Equity Bonus target

Full description

Minimum qualifications:

  • Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
  • 6 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, retrieval-augmented generation (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:

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 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: $152000 - $221000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google. 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.

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