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 technical wins for complex Gemini enterprise workloads to ensure rapid adoption, supporting the business cycle from evaluation through customer ramp, while recommending integration strategies, enterprise architectures, platforms, and application infrastructure for Google Cloud solutions.
- Combine business strategies with direct development and prototyping to provide functional, customer-tailored solutions that secure buy-in from domain experts.
- Provide deep technical consultation on enterprise AI integration patterns, acting as a trusted advisor, using these engagements to build reusable Go-To-Market (GTM) assets and channel critical customer feedback to Product and Engineering teams.
- Build and demonstrate integrations directly with Google Cloud products, leveraging Product and Engineering management systems to document, prioritize, and drive resolution of feature requests and issues.
- Travel to customer sites, conferences, and events as required, acting as a public advocate for Google Cloud.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 4 years of experience with cloud native architecture in a customer-facing or support role.
- Experience with cloud engineering, on-premise engineering, virtualization, or containerization platforms.
- Experience engaging with, or presenting to, technical stakeholders or executive leaders.
- Experience in programming languages, debugging, systems design, prototyping, demos, or customer workshops.
- Ability to communicate in English and Korean fluently as this is a customer-facing role that requires interactions with local stakeholders.
Preferred qualifications:
- Master's degree in Computer Science, Engineering, Mathematics, a technical field, or equivalent practical experience.
- Experience developing agents using frameworks like LangGraph, Semantic Kernel, or Google AI Agent Development Kit (ADK).
- Experience with functional evaluation metrics used to assess model quality and agent quality.
- Understanding 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.