Join Google Cloud as an AI Customer Engineer and empower leading companies to harness the transformative power of cloud computing. You'll be instrumental in facilitating the adoption of Google Cloud products, making client operations more productive, mobile, and collaborative. This role involves actively listening to customer needs and delivering impactful solutions. You will collaborate with sales teams to resolve complex technical challenges and work closely with product marketing and engineering to stay ahead of industry trends, driving enhancements for Google Cloud.

Our AI Go-To-Market (GTM) team within Google Cloud, specializing in Information Technology Enabled Services (ITES), acts as trusted AI advisors. We aim to create next-generation business transformations for our clients by offering AI expertise, thought leadership, and industry best practices to revolutionize customer outcomes.

Drive technical solutions for intricate AI workloads, ensuring rapid and successful customer adoption from technical evaluation through implementation.

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

Provide expert technical consultation, serving as a trusted advisor and cultivating strong customer relationships.

Contribute to reusable solutions and assets for 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.

Document, prioritize, and drive the resolution of customer feature requests and technical issues within product and engineering management systems.

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

Six years of experience working with ITES clients is essential.

Demonstrated experience in engaging with and presenting to technical stakeholders and executive leaders is a must.

Preferred qualifications include experience developing financial services or telecommunication agents using frameworks like LangGraph or Semantic Kernel, alongside expertise in cloud technologies such as SaaS, iPaaS, business automation, and Agentic AI. Knowledge of integration patterns and observability constructs for AI applications is also beneficial.