Cloud Conversational AI Engineer, Google Cloud (English, Italian)


Milano, Milan, Italy



Nov 15


Google welcomes people with disabilities.

Minimum qualifications:

  • Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
  • Experience coding in one or more languages such as Python, Java, or similar.
  • Experience building conversational applications with Dialogflow or similar products.
  • Ability to communicate in English and Italian fluently.

Preferred qualifications:

  • Experience building applications powered by Large Language Models.
  • Experience in technical consulting.
  • Understanding of contact center technologies and platforms (e.g. Avaya, Genesys, Cisco, Mitel, Twilio, etc.).

About the job

The Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate.

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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.


  • Be a trusted technical advisor to customers and solve Machine Learning challenges.
  • Create and deliver recommendations, tutorials, blog articles, sample code, and technical presentations adapting to different levels of key business and technical stakeholders.
  • Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
  • Coach customers on the practical challenges in ML systems (e.g., feature extraction, feature definition, data validation, monitoring, and management of features/models). 
  • Travel regularly (up to 30%, although we also frequently use video conferencing) in-region for meetings, technical reviews, and onsite delivery activities as needed.

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