구글(Google) - Forward Deployed Engineer, Gen AI, Google Cloud

회사 소개

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. In this role, you will be an embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customers. You will manage blocker to production including solving the integration complexities, data readiness issues, and state-management tests that prevent AI from reaching enterprise-grade maturity.

주요 업무

• Serve as the lead developer for AI applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, master control program (MCP) servers) that drive return on investment (ROI).
• Architect and code the connective tissue between Google's AI products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters.
• Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
• Identify repeatable field patterns and technical 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 development best practices, ensuring project success and end-user adoption.

자격요건

• Bachelor's degree in a Science, Technology, Engineering, and Mathematics or a related field, or equivalent practical experience.
• 6 years of experience in providing production-grade AI solutions to external or internal customers with L400-level in Python, and architecting AI systems on cloud platforms.
• Experience developing Generative AI (Gen AI) solutions with foundation models, first-party model tuning, and advanced retrieval-augmented generation (RAG) architectures.

우대사항

• Master's degree or PhD in Artificial Intelligence, Computer Science, or a related technical field.
• Experience in implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google's Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.
• Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• Ability to implement agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.
• Ability to build full-stack applications that interact with enterprise IT infrastructures, and perform interviews to find the business problem and translate hardware/AI constraints for technical teams.

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