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 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.
