AI Customer Engineer, Retail, Google Cloud

• Drive the technical solution for complex workloads within AI product areas to ensure rapid and successful adoption, primarily supporting the sales cycle from technical evaluation through customer ramp.
• Combine sales strategies and direct development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
• Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships. Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team.
• 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 in a technical field or equivalent practical experience.
• 10 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 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.

Preferred qualifications:

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

• Bachelor's degree in a technical field or equivalent practical experience.
• 10 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 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.