Practice Customer Engineer, Cloud AI

Practice Customer Engineer, Cloud AI

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.

As a Practice Customer Engineer, Cloud AI, you will partner with technical business teams to differentiate Google Cloud to the customers. You will serve as the technical authority on integrating Generative Artificial Intelligence (AI) into enterprise environments, moving beyond simple chat interfaces to architecting secure and data-connected solutions. You will engage with customers to understand their business and technical requirements, and present solutions on Google Cloud. You will blend market knowledge and technical engagement to show the value of the Google Cloud AI portfolio.

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.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer-facing or support role.
• Experience with search systems including retrieval, ranking, and search quality tuning.
• Experience with presenting to technical stakeholders and executive leaders.
• Experience in architecting solutions that integrate AI models using agents with enterprise data sources using patterns like Retrieval-Augmented Generation (RAG), Text-to-SQL, and semantic search.
• Experience with coding in Python, JavaScript, TypeScript, Go, or Java, to demo, prototype, or workshop integration patterns with customers.

Preferred qualifications:

• Experience developing agents using frameworks such as langgraph, semantic kernel, or Google AI Agent Development Kit (ADK).
• Experience with functional evaluation metrics used to assess model quality and agent quality.
• Experience with iPaaS, API gateways, or enterprise service buses in a cloud environment.
• Knowledge of integration patterns using OpenAPI and Model Context Protocol (MCP) to connect AI agents with business systems and Application Programming Interface (API) gateways.
• Knowledge of observability constructs including distributed tracing, logging, and audit logging for AI applications.
• Knowledge of application integration governance and security, including OAuth2 flows and short-lived credential management.

Responsibilities:

• Drive the technical workloads within Gemini enterprise to ensure adoption, supporting the business cycle from technical evaluation through customer ramp.
• Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud.
• Combine sales strategies with development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
• Provide technical consultation to customers on enterprise AI integration patterns, acting as a technical advisor and building customer relationships.
• Work with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
• Work within product and engineering management systems to document, prioritize, and drive resolution of customer feature requests and issues.
• Travel to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud.

Key skills/competency:

• Generative AI
• Cloud Native Architecture
• Enterprise AI Integration
• Retrieval-Augmented Generation (RAG)
• Python/Java/Go/JavaScript
• Solution Architecture
• Customer Consulting
• API Gateways
• Search Systems
• Technical Prototyping