AI Customer Engineer, Google Cloud

About the job

Leading with the future, the AI GTM Information Technology Enabled Servives (ITES) Google Cloud team are trusted AI advisors, expanding across Google to deliver transformative customer experiences that shape the next generation of their business. Partnering to provide AI expertise, thought leadership, and industry best practices, we revolutionize customer outcomes.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.

Responsibilities

• Drive the technical solution for complex workloads within AI product areas to ensure rapid and successful adoption, primarily supporting the business cycle from technical evaluation through customer ramp.
• Combine business strategies and direct development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
• Provide technical consultation to customers, acting as a technical advisor and building customer relationships.
• Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go-to-Market team. Travel to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud.
• Work within product and engineering management systems to document, prioritize and drive resolution of customer feature requests and issues.

Qualifications

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 6 years of experience working within tech startups or digital-native organizations.
• Experience engaging with, and presenting to, technical stakeholders and executive leaders.

Preferred qualifications:

• Experience in developing financial services or telecommunication agents using frameworks such as LangGraph, Semantic Kernel, or the Google AI Agent Development Kit (ADK).
• Experience with cloud technologies including SaaS applications, iPaaS, business automation solutions, Cloud infrastructure, Agentic AI, and cloud networking.
• 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.