Senior AI Solutions Architect, Generative AI, Google Cloud

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience in technical project management, stakeholder management, professional services, solution engineering or technical consulting, and 4 years of experience in technical leadership.
• 2 years of experience writing code in one or more programming languages.
• 1 year of experience in technical troubleshooting.
• Ability to communicate in English and Spanish fluently as this is a customer-facing role that requires interactions in English and Spanish with local stakeholders.

Preferred qualifications:

• Experience in designing and deploying with one or more of the following ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.
• Experience in training and fine tuning models in large-scale environments (e.g., image, language, recommendation) with accelerators.
• Experience with CI/CD solutions in the context of MLOps and LLMOps, including automation with IaC (e.g., using terraform).
• 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.

About the job

As an Executive AI Solutions Architect, you will lead Google Cloud sales and engineering teams to incubate, pilot, and deploy Google Cloud’s industry leading AI/ML and Generative AI technology with AI natives, large enterprises, and early-stage AI startups. You will help customers innovate faster with solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators (e.g., TPU/GPU).

In this role, you will identify, assess, and develop Generative AI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. You will work closely with internal Cloud AI teams to remove roadblocks and shape the future of our 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.

In this role, you will identify, assess, and develop Generative AI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. You will work closely with internal Cloud AI teams to remove roadblocks and shape the future of our offerings.

Responsibilities

• Be a trusted advisor to our customers by understanding the customer’s business process and objectives. Architect AI-drive spanning data, AI and Infrastructure, and work with peers to include the full cloud stack into overall architecture.
• Demonstrate how Google Cloud is differentiated by working with customers on POCs, demonstrating features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues training/serving models in a large-scale environment.
• Build repeatable technical assets such as scripts, templates, reference architectures to enable other customers and internal teams. 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 activities.