Field Solutions Architect, Generative AI

1 Month ago • 5 Years + • Artificial Intelligence

Job Summary

Job Description

As a Field Solutions Architect for Generative AI at Google Cloud, you'll advise customers, design GenAI solutions encompassing AI, data, and infrastructure, and collaborate with peers to integrate the full cloud stack into architecture. You'll demonstrate Google Cloud's GenAI features, optimize model performance, and build reusable technical assets (scripts, templates, etc.). Responsibilities include troubleshooting GenAI applications, influencing Google Cloud strategy by advocating for customer needs, coordinating regional field enablement, and collaborating with product and partner organizations. You'll work with AI natives, large enterprises, and startups, leveraging Google Cloud's AI Accelerators (TPU/GPU) to help customers innovate faster.
Must have:
  • 5+ years AI experience (deep learning, NLP, CV)
  • Python, ML techniques, TensorFlow/PyTorch
  • Technical presentations & business value sessions
  • Design & deploy GenAI solutions
  • Troubleshoot GenAI applications
Good to have:
  • Master's degree in CS/Engineering
  • Experience with JAX, Spark ML
  • Large-scale model training with accelerators
  • Distributed training & cost optimization
  • CI/CD, MLOps, LLMOps, IaC (Terraform)
  • Data pipeline & ML pipeline design

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience in artificial intelligence applications such as deep learning, natural language processing, computer vision, or pattern recognition.
  • Experience in Python, applied machine learning techniques, and using OSS frameworks (i.e., TensorFlow, PyTorch).
  • Experience delivering technical presentations and leading detailed business value sessions.

Preferred qualifications:

  • Master's degree in Computer Science, Engineering, or a related technical field.
  • Experience designing and deploying with one or more from the following ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.
  • Experience training and fine tuning models in large-scale environments (i.e., 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.

About the job

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As an AI Field Solutions Architect, your experience and thought leadership will support Google Cloud sales teams and engineering incubate, pilot, and deploy Google Cloud’s industry leading AI and GenAI technology at AI natives and innovators, large enterprises, and early stage AI startups. You will help customers innovate faster with state of the art solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators (TPU/GPU). In this role, you will identify, assess, and develop GenAI 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.

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.

Responsibilities

  • Be a trusted advisor to our customers by understanding the customer’s business process and goals. Design Generative AI-driven solutions, spanning AI, data, 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 application prototypes, demonstrating Generative AI features, prompting and tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues in Generative AI applications.
  • Build repeatable technical assets such as scripts, templates, reference architectures, etc. to enable 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 with product and partner organizations on external enablement. Travel as needed.

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