Customer Engineer Cloud AI
Job Overview
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Job Description
Overview
At Google, our vision is to empower every individual and organization. As a Customer Engineer Cloud AI, you will be the technical authority in integrating Generative AI into enterprise environments, partnering with Sales teams and engaging with customers to shape innovative, secure, and data-connected solutions on 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.
- Proficiency in Python, JavaScript/TypeScript, Go, or Java.
- Experience with search systems, retrieval, ranking, and quality tuning.
- Demonstrated ability to present technical solutions to stakeholders and executives.
Preferred Qualifications
- Experience developing agents using frameworks like langgraph or Google AI ADK.
- Familiarity with iPaaS, API Gateways or ESBs in a cloud environment.
- Understanding evaluation metrics for AI model and agent quality.
- Knowledge of observability, distributed tracing, logging and audit logging.
- Expertise in application integration governance including short-lived credential management.
About the Role
The Google Cloud Platform team transforms businesses using reliable, secure, and scalable cloud technologies. As a Practice Customer Engineer specializing in Gemini Enterprise, you will:
- Drive technical wins for workloads, from evaluation to ramp-up.
- Recommend enterprise architectures and integration strategies.
- Provide technical consultation and develop prototypes for customers.
- Engage directly with customer and partner environments using Google Cloud products.
- Travel for customer engagements, conferences, and events.
Key skills/competency
Cloud Native, Integration, AI, Enterprise, Generative, Prototype, Sales Support, Python, API, Security
How to Get Hired at Google
- Research Google's culture: Understand mission, values, and recent initiatives.
- Tailor your resume: Emphasize cloud-native and AI integration skills.
- Showcase technical expertise: Highlight relevant coding and architecture experience.
- Prepare for interviews: Review enterprise and technical case studies.
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