Forward Deployed Engineer, Generative AI, Google Cloud (Korean, English)

As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as an 'innovator-builder,' moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer's environment. This role is designed for high-agency engineers with a founder's mindset.

• Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI).
• Architect and code the 'connective tissue' between Google's AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
• Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
• Identify repeatable field patterns and friction points in Google's AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
• Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
• Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 2 years of experience with software development using Python or similar coding languages.
• Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).
• Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
• Ability to communicate in Korean and English fluently to conduct necessary business interaction in Korean and English.
• Master's degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
• Experience leading technical discovery sessions.
• Knowledge of 'LLM-native' metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

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