Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 6 years of experience with cloud native architecture in a customer-facing or support role.
- Experience of building and deploying Generative AI solutions.
- Experience engaging with, and presenting to, technical stakeholders and executive leaders
- Master's degree in Computer Science, Engineering, Mathematics, a technical field.
- Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g. deep learning, LSTM, convolutional networks).
- Experience in architecting and developing software or infrastructure for scalable, distributed systems.
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About the job
Through Google.org we invest millions each year in game-changing ideas to make the world a better place. We support innovative technologies and entrepreneurial approaches that take on tough human challenges and scale to help millions of people.
As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Analytics and AI, helping retail customers with Vertex based retail solutions using Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business challenges, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks.
Responsibilities
- Work with the Sales team to get the best out of Google Cloud for our customers. Explain technical features and problem-solving any potential roadblocks.
- Work with the team to identify and qualify business opportunities, identify key customer technical objections, and develop the strategy to resolve technical blockers.
- Own the technical relationship with Google's customers, including managing product and solution briefings, proof-of-concept work, and the coordination of additional technical resources.
- Recommend integration strategies, enterprise architectures, platforms and application infrastructure required to successfully implement a complete solution using best practices on Google Cloud.
- Work directly with Google Cloud products and Retail AI Solutions (e.g. Vertex AI Search for Retail) to demonstrate and prototype integrations in customer and partner environments.