Field Solutions Architect III, Generative AI, Google Cloud

Minimum qualifications:

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 8 years of experience in Python or other programming languages common in machine learning (e.g., Java, C++, Go).
• Experience in applied AI, with a focus on designing and evaluating systems around foundation models. This includes prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and orchestrating model interactions with external tools to deliver complete solutions.
• Experience architecting, deploying, or managing solutions on a Cloud Platform (e.g., Google Cloud Platform (GCP)).

Preferred qualifications:

• 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.
• Experience in software engineering management or project/program management.
• Ability to apply strategic product insights to solve immediate customer tests and unlock long-term value.

About the job

As a Field Solutions Architect, you will play a pivotal role in the Google Cloud AI Go-To-Market organization. You will be focused on frontier AI, including Generative AI (GenAI), in a highly-technical customer-facing role. Your primary responsibility will be to construct prototype Generative AI applications tailored to Google Cloud customers, catering to a clientele ranging from early stage startups to prominent, established companies. You will be a hybrid professional, blending the core competencies of an engineer with an aptitude for customer engagement and strategic problem-solving. You will lead with deep, bespoke implementation as the primary value proposition, ensuring that our core technology delivers demonstrable value in the customer's unique operational context.

You will have close collaboration with our Product and Engineering teams to eliminate obstacles and shape the future trajectory of our offerings. You will be adept at disseminating lessons learned to customers and internal Google teams, translating one-off customer solutions into reusable, scalable assets.

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.

The US base salary range for this full-time position is $177,000-$263,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Be a trusted advisor to our customers by understanding the customer’s business process and objectives. Design, lead and execute Generative AI-driven projects, spanning AI, Data, and Infrastructure, and work with peers to include the full cloud stack into overall architecture.
• Build production-grade prototypes that deliver measurable outcomes.
• Gather real-time feedback and insights. Formalize and abstract field-tested solutions into reusable modules or new core product features to drive product innovation.
• 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, backed up with real-world data from your engagements.
• Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement. Travel as needed.