Join Google Cloud's Go-To-Market team and lead the AI revolution for businesses globally. You'll leverage Google's trusted brand and cutting-edge AI portfolio, including Gemini models and the Vertex AI platform, to address complex business challenges. Collaborate directly with DeepMind engineers and researchers to empower customer success and shape the future of cloud technology.

As an AI Customer Engineer, you will partner closely with technical sales teams to showcase the power of Google Cloud and drive the adoption of specialized, complex AI workloads. You'll act as a trusted technical advisor, accelerating wins and accelerating customer adoption.

This role offers a unique opportunity to work with advanced AI technologies and contribute to the growth of businesses by solving their most pressing problems with cloud solutions.

Drive technical solutions for intricate AI workloads, ensuring swift and successful customer adoption from evaluation to ramp-up.

Integrate business strategies with hands-on development and prototyping to deliver tailored, functional solutions that gain approval from customer domain experts.

Offer in-depth technical guidance to clients, serving as a key advisor and cultivating robust customer relationships. Share insights from engagements to build reusable assets for the Go-To-Market team.

Collaborate with product and engineering teams to document, prioritize, and resolve customer feature requests and issues.

Represent Google Cloud at customer sites, conferences, and other events, acting as a strong advocate for our platform.

A Bachelor's degree in a technical field or equivalent practical experience is required.

Six years of experience in cloud-native architecture within a customer-facing capacity is essential.

Proven experience architecting solutions that effectively integrate AI models with enterprise data sources using patterns like RAG, Text-to-SQL, and semantic search.

Proficiency in coding languages such as Python, JavaScript, TypeScript, Go, or Java to create demos, prototypes, and conduct workshops for customers.

Experience with frameworks like LangGraph, Semantic Kernel, or the Google AI Agent Development Kit (ADK) is preferred.

Familiarity with cloud technologies including SaaS, iPaaS, business automation, cloud infrastructure, agentic AI, and cloud networking is advantageous.

Experience engaging with and presenting to technical stakeholders and executive leadership is a plus.