About the job:
When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
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.
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.
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