Join Google Cloud as an AI Customer Engineer, spearheading transformative AI solutions for ITES clients. This role is pivotal in enabling leading companies to harness the power of cloud computing globally, driving productivity, mobility, and collaboration. You will be instrumental in solving complex technical challenges and contributing to the evolution of Google Cloud products by liaising with product marketing and engineering teams.

As a trusted AI advisor within the AI GTM, Information Technology Enabled Services (ITES) Google Cloud team, you will pioneer next-generation business experiences. Your expertise will revolutionize customer outcomes through AI, thought leadership, and best practices, accelerating digital transformation for organizations worldwide.

Google Cloud empowers businesses across over 200 countries and territories with enterprise-grade solutions. We leverage Google's advanced technology to help developers build more sustainably and solve their most critical business problems, making us a trusted partner for growth.

Spearhead the technical solution for complex AI workloads, ensuring swift and successful customer adoption from technical evaluation to implementation.

Develop and prototype customer-tailored solutions by integrating business strategies, gaining buy-in from domain experts.

Serve as a technical advisor to customers, fostering strong relationships and providing expert consultation.

Contribute reusable solutions and assets to the Go-to-Market team based on customer engagement insights.

Act as a public advocate for Google Cloud by traveling to customer sites, conferences, and events as needed.

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

A Bachelor's degree or equivalent practical experience is required.

Minimum of 6 years of experience working directly with ITES clients is essential.

Proven ability to engage with and present technical information to both technical stakeholders and executive leaders.

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

Familiarity with cloud technologies including SaaS applications, iPaaS, business automation, cloud infrastructure, Agentic AI, and cloud networking is beneficial.

Knowledge of integration patterns using OpenAPI and Model Context Protocol (MCP) to connect AI agents with business systems and API Gateways is advantageous.

Understanding of observability constructs like distributed tracing, logging, and audit logging for AI applications is a plus.