Customer Engineer, Data Analytics and Artificial Intelligence

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 with Machine Learning and Data Analytics products.
  
• Experience engaging with and presenting to technical stakeholders and executive leaders.
  

Preferred qualifications:

• Master's degree in Computer Science, Engineering, Mathematics, a technical field, or equivalent practical experience.
  
• Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g.,deep learning, Long short-term memory (LSTM), convolutional networks).
  
• Experience in data and information management as it relates to big data trends and issues within businesses.
  
• Experience in architecting and developing software or infrastructure for scalable, distributed systems.
  
• Ability to learn, understand and work with new emerging technologies, methodologies, and solutions in the cloud/IT technology space.
  

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.

Responsibilities

• Help customers and partners in understanding the power of Google Cloud, explaining technical features and problem-solving any potential roadblocks.
• Work with the team to identify and qualify business opportunities, 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 technical resources.
• Recommend integration strategies, enterprise architectures, platforms and application infrastructure required to successfully implement a complete solution using best practices on Google Cloud.