Field Solutions Architect Iii, Generative Ai, Google Public Sector

Google Google · Big Tech · Reston, VA +3

Field Solutions Architect for Google Public Sector, focusing on building rapid prototype generative AI applications for public sector customers. This role involves leveraging generative AI technologies, collaborating with product teams, and disseminating lessons learned. Responsibilities include designing end-to-end genAI solutions, demonstrating Google Cloud capabilities, building repeatable technical assets, and influencing product direction. Requires experience in applied AI with foundation models, prompt engineering, fine-tuning, RAG, and orchestrating model interactions, along with cloud platform experience and a security clearance.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement. Travel as needed.

Skills

Required

  • Python or other programming languages in machine learning (e.g., Java, C++, Go)
  • 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)
  • Architecting, deploying, or managing solutions on a cloud platform
  • Top Secret/SCI security clearance

Nice to have

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

What the JD emphasized

  • Active, or the ability to obtain, Top Secret/SCI security clearance.

Other signals

  • Generative AI
  • Foundation Models
  • Prompt Engineering
  • Fine-tuning
  • RAG
  • Orchestrating model interactions
  • Customer-facing solutions
  • Prototyping
  • Technical assets