As a Generative AI (GenAI) Forward Deployed Developer at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customer environments. Unlike traditional advisory roles, you will function as a builder-consultant, moving beyond architecture to code, debug, and jointly ship bespoke agentic solutions. You will solve the integration complexities, data readiness, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment and acting as a critical feedback loop for Google Cloud's future product roadmap. Responsibilities Lead the Discovery-to-Deployment journey as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows that drive measurable ROI. Bridge the enterprise gap by coding the connective tissue between Google's AI products and customer live infrastructure, including APIs, legacy data silos, and security perimeters. Drive production excellence by building evaluation pipelines and observability frameworks to ensure agentic systems meet accuracy, safety, and latency requirements. Act as a product catalyst by identifying repeatable field patterns and technical friction points in Google's AI stack, converting them into reusable modules or product feature requests. Drive regional leadership and upskilling by mentoring talent, co-building with customer teams, and influencing cross-functional strategies. Minimum Qualifications Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 8 years of experience shipping production-grade AI-powered solutions to external or internal customers. Experience in Python. Experience developing AI systems on cloud platforms. Experience building full-stack solutions that interface with enterprise systems. Experience managing technical discovery sessions with executive stakeholders (C-suite) and development teams to define AI and hardware infrastructure requirements. Preferred Qualifications 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, or Google's ADK) and patterns like ReAct, self-reflection, and hierarchical delegation. Knowledge of LLM-native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. Ability to implement secure agentic workflows incorporating Model Context Protocol (MCP), tool-calling, and OAuth-based authentication. Bachelor's degree in a technical field or equivalent experience; 8+ years shipping production-grade AI solutions; proficiency in Python; experience with cloud platforms, full-stack enterprise development, and C-suite stakeholder management. #J-18808-Ljbffr