Generative AI Field Solution Architect, Google Cloud - Job Opportunity

Company Name: Google

Minimum Qualifications

Bachelor's degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.

5 years of experience in Artificial Intelligence applications (e.g., deep learning, natural language processing, computer vision, or pattern recognition).

Experience delivering technical presentations and leading business value sessions.

Experience working with programming languages (e.g. Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch).

Fluency in English and Korean, as this is a customer-facing role requiring interactions in both languages with local stakeholders.

Preferred Qualifications

Master's degree in Computer Science, Engineering, or a related technical field.

Experience designing and deploying with one or more ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.

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 with CI/CD solutions in the context of MLOps and LLMOps, including automation with IaC (e.g., using Terraform).

Experience in systems design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.

Experience in building and deploying large-scale machine learning models with a focus on accuracy and efficiency.

About the Job

As a Generative AI Field Solutions Architect, you will support Google Cloud Sales and Engineering teams to incubate, pilot, and deploy Google Cloud’s AI/ML and Generative AI technology with AI-native customers, large enterprises, and early-stage AI startups. Your role is pivotal in helping customers innovate using Google Cloud’s flexible and open infrastructure, including AI Accelerators (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 ratios.

Throughout your journey, you will collaborate closely with internal Cloud AI teams to overcome obstacles 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 to help developers build more sustainably. Customers in over 200 countries and territories turn to Google Cloud as their trusted partner to foster growth and tackle their most critical business challenges.

Responsibilities

Be a trusted advisor to our customers by understanding their business processes and goals. Architect AI-driven solutions spanning Data, AI, and Infrastructure, and collaborate with peers to integrate the full cloud stack into the overall architecture.

Demonstrate Google Cloud's differentiation by working with customers, showcasing features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and resolve issues with training/serving models in a large-scale environment.

Build repeatable technical assets (e.g., scripts, templates, reference architectures, etc.) 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 collaborate closely with product and partner organizations on external enablement activities.