Become a Generative AI Forward Deployed Engineer (FDE) at Google Cloud, an embedded builder who transforms cutting-edge AI products into production-ready solutions for clients. This role is for high-agency engineers with an entrepreneurial spirit, focusing on coding, debugging, and deploying bespoke agentic solutions directly within customer environments. You will tackle integration challenges, data readiness, and state management to achieve enterprise-grade AI maturity. Embed with strategic accounts to provide expert AI system deployment and act as a vital feedback channel, influencing Google Cloud's future product roadmap with real-world insights.

Join Google Cloud's Go-To-Market team and lead the AI revolution for businesses. Leverage Google's trusted brand and advanced AI portfolio, including Gemini models and the Vertex AI platform, to solve complex business problems. Collaborate with DeepMind's engineering and research teams to drive customer success and define the next era of cloud computing.

Develop complex AI applications, evolving from rapid prototypes to production-grade agentic workflows like multi-agent systems and model context protocol (MCP) servers, ensuring measurable return on investment.

Architect and implement the essential connections between Google's AI products and customer infrastructure, including APIs, legacy data, and security perimeters, as part of an expert team.

Build robust evaluation pipelines and observability frameworks to guarantee agentic systems meet stringent accuracy, safety, and latency requirements.

Identify recurring field challenges and patterns within Google’s AI stack, translating them into reusable modules or formal feature requests for engineering teams.

Collaborate with customer engineering teams to embed Google-grade development best practices, fostering long-term project success and high end-user adoption.

A Bachelor's degree in Engineering, Computer Science, or a related field, or equivalent practical experience is required.

Possess 8 years of experience in cloud computing or a technical customer-facing role.

Demonstrated experience in building data pipelines for structured and unstructured data, utilizing vector databases and RAG architectures for enterprise AI solutions.

Proven track record of taking production-grade AI solutions from concept to launch, and architecting AI systems on cloud platforms like Google Cloud Platform (GCP).

Experience leading technical discovery sessions is essential.