Field Solutions Architect II, Google Cloud, Generative AI

GoogleAddison, TX
2d$147,000 - $216,000Hybrid

About The Position

As a Field Solutions Architect in the Google Cloud AI Go-To-Market team, you will bridge the gap between frontier AI products and real-world business issues. You will lead technical delivery from initial discovery to architecting and deploying GenAI solutions on customer infrastructure. This role requires a blend of engineering expertise and customer engagement. You will build rapid prototypes for a clientele, ranging from startups to global enterprises, while collaborating with Product and Engineering teams to scale custom solutions into reusable assets. In this role, you will drive the adoption of Google Cloud’s GenAI offerings by delivering bespoke, high-value implementations. You are responsible for constructing rapid prototypes that demonstrate the operational value of our technology in unique customer contexts. Beyond technical delivery, you will influence the future product roadmap by translating field insights into scalable engineering requirements. This hybrid position requires deep technical skill, problem-solving, and a commitment to customer-centric innovation. The Field Solutions Architect is a hybrid engineering and customer-facing role focused on deploying Generative AI solutions. You will own the technical delivery for Google Cloud customers, building tailored prototypes that solve business problems, by collaborating with internal Product teams and external stakeholders, you will eliminate technical obstacles and turn custom implementations into scalable, global offerings.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Requirements

  • Bachelor's degree in Science, Technology, Engineering, Mathematics, or a related technical field or equivalent practical experience.
  • 6 years of experience in Python and relevant machine learning packages (e.g., Keras, Pytorch, HF Transformers).
  • Experience in applied AI, with a focus on designing 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.

Nice To Haves

  • Master's degree in Computer Science, Engineering, or a related technical field.
  • Experience training and fine tuning models in large scale environments (e.g., image, language, recommendation) with accelerators.
  • Experience with distributed training and optimizing performance versus costs.
  • Experience in systems design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.
  • Ability to apply a founder-level engineering mentality to prioritize rapid action and resolve customer issues.

Responsibilities

  • Be a trusted advisor to customers by understanding their business process and objectives. Design and build GenAI-driven solutions spanning AI, Data, and Infrastructure. Work with peers to include the full cloud stack into overall architecture.
  • Build production-grade prototypes that deliver measurable outcomes (e.g., write custom code, integrate disparate data sources, design data ontologies, deploy solutions on customer infrastructure).
  • Represent the customer, gathering real-time feedback and insights. Formalize and abstract field-tested solutions into reusable modules or new product features to drive product innovation. Establish technical and business cases to support recommendations.
  • Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for 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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