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Listing record updated: September 23, 2026. We archive records after 60 days without an update. This date does not confirm that the employer is still hiring.

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About the position

This role partners with technical sales teams to differentiate Google Cloud for customers. The Customer Engineer acts as a technical expert to accelerate technical wins and adoption of specialized workloads. Responsibilities include writing code, developing prototypes, and demos to promote solutions. The position requires solving AI-centered customer issues and providing feedback to influence product development. The role blends sales skills with technical engagement to prove the value of the Google Cloud portfolio.

Responsibilities

Drive the technical solution for complex workloads within AI product areas to ensure rapid and successful adoption.

Combine business strategies and direct development and prototyping to provide functional, customer-tailored solutions.

Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships.

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.

Requirements

Bachelor's degree in a technical field or equivalent practical experience.

6 years of experience with cloud native architecture in a customer-facing or support role.

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 or TypeScript, Go, or Java, to demo, prototype, or workshop integration patterns with customers.

Ability to communicate in Thai and English fluently to support client relationship management.

Nice to have

Experience with cloud technologies including SaaS applications, iPaaS, business automation solutions, cloud infrastructure, Agentic AI, and cloud networking.

Experience engaging with, or presenting to, technical stakeholders or executive leaders.

Knowledge of observability constructs including distributed tracing, logging, and audit logging for AI applications.

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