Join Google Cloud's Go-To-Market team as an AI Customer Engineer and lead the AI revolution for businesses globally. Leverage Google's cutting-edge AI portfolio, including Gemini models and the Vertex AI platform, to address complex business challenges. Collaborate with DeepMind's engineering and research teams to drive customer success and shape the future of cloud technology.

As a key member of an entrepreneurial team within this rapidly expanding sector, you'll play a pivotal role in understanding client needs and influencing how businesses of all sizes utilize technology to connect with their customers, employees, and partners. This role is central to accelerating technical wins and driving adoption of sophisticated, specialized workloads.

This position offers the opportunity to be at the forefront of cloud innovation, making a tangible impact on how businesses operate and grow through advanced AI solutions.

- Drive technical solutions for intricate AI workloads, ensuring swift and successful customer adoption from initial evaluation through ramp-up. - Develop tailored, functional customer solutions by integrating business strategies with direct development and prototyping, gaining buy-in from customer domain experts. - Offer in-depth technical guidance to clients, serving as a trusted advisor and cultivating robust, long-term relationships. - Share insights from customer engagements to enhance reusable solutions and assets within the Go-To-Market team. - Collaborate with Product and Engineering management to document, prioritize, and resolve customer feature requests and technical issues. - Travel to customer sites, industry events, and conferences as needed, acting as a public advocate for Google Cloud.

We are seeking individuals with a Bachelor's degree in a technical field or equivalent practical experience, coupled with at least six years of experience in cloud-native architecture within a customer-facing capacity.

Demonstrated expertise in architecting solutions that integrate AI models with enterprise data sources using patterns like RAG, Text-to-SQL, and semantic search is essential. Proficiency in coding with Python, JavaScript, TypeScript, Go, or Java is required to build demonstrations, prototypes, and workshops for clients.

Preferred qualifications include experience developing AI agents with frameworks such as LangGraph or Semantic Kernel, and familiarity with cloud technologies including SaaS, iPaaS, business automation, cloud infrastructure, agentic AI, and networking. Experience presenting to technical stakeholders and executives, along with knowledge of integration patterns using OpenAPI and MCP, is highly valued.