Join Google Cloud as a Generative AI Forward Deployed Engineer and become a key player in bridging cutting-edge AI products with real-world production environments for our customers. This unique "innovator-builder" role goes beyond architecture, focusing on coding, debugging, and collaboratively deploying bespoke agentic solutions directly within customer systems. It's an ideal position for high-agency engineers possessing a "founder’s mindset" to tackle complex integration, data readiness, and state-management challenges, enabling AI to achieve enterprise-grade maturity. By embedding with strategic accounts, you will not only provide "white glove" deployment of sophisticated AI systems but also serve as a vital feedback channel, influencing Google Cloud’s future product roadmap with invaluable field insights. Seize this opportunity to lead the AI revolution for businesses globally, leveraging Google's legacy of technological innovation and our world-class AI portfolio, including Gemini models and the Vertex AI platform. Collaborate closely with engineering and research minds from DeepMind to solve critical customer challenges and redefine the cloud era.

As a Generative AI Forward Deployed Engineer, you will:

- Develop complex AI applications, transforming rapid prototypes into production-ready agentic workflows, such as multi-agent systems and model context protocol (MCP) servers, to deliver measurable return on investment (ROI). - Engineer the critical "connective tissue" that seamlessly integrates Google's AI products with customers' live infrastructure, including APIs, legacy data silos, and security perimeters, as part of an expert team. - Construct high-performance evaluation pipelines and robust observability frameworks to guarantee agentic systems meet stringent requirements for accuracy, safety, and latency. - Identify recurring field patterns and integration friction points within Google’s AI stack, translating them into reusable modules or formal feature requests for the Engineering teams. - Collaborate closely with customer engineering teams to implement Google-grade development best practices, fostering long-term project success and maximizing end-user adoption.

We are seeking individuals with a Bachelor’s degree in Engineering, Computer Science, or a related field, or equivalent practical experience. A minimum of 8 years of experience in cloud computing or a technical customer-facing role is essential.

Key technical proficiencies include: - Building data pipelines for both structured and unstructured data utilizing vector databases and RAG-like architectures to power enterprise AI solutions. - Successfully transitioning production-grade AI-driven solutions from concept to launch. - Architecting AI systems on cloud platforms, with a strong preference for Google Cloud Platform (GCP). - Leading technical discovery sessions effectively.

Preferred qualifications include a Master’s or PhD in AI, Computer Science, or a related technical field, alongside experience implementing multi-agent systems using frameworks like LangGraph or CrewAI, and familiarity with complex patterns such as ReAct. Knowledge of "LLM-native" metrics and techniques for optimizing state management and granular tracing is also advantageous.