Practice Customer Engineer, Cloud AI, Google Cloud - Jakarta, Bangkok or Singapore

Product area

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.

Job description

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.

Additional job description

As a Practice Customer Engineer (CE) with a specialty in Gemini Enterprise, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your deep expertise in our most strategic product areas, in partnership with Platform CEs, to be hands-on writing code to developing prototypes, proofs-of-concept, and demos to sell new, highly specialized solutions to customers. You will solve AI-centered customer challenges and provide a critical feedback loop to influence product development.

You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales prowess, market knowledge, and hands-on technical engagement to prove the value of the Google Cloud portfolio.

Qualifications

Job responsibilities

• Drive the technical win for 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 business 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.

Minimum qualifications

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

Preferred qualifications

• Experience in developing agents using frameworks such as LangGraph, Semantic Kernel, or the 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 Application Integration Governance and Security, including OAuth2 flows and short-lived credential management.
• Knowledge of observability constructs including distributed tracing, logging, and audit logging for AI applications.