Join Google Cloud as a Customer Engineering Manager, focusing on the Manufacturing and Conglomerates sector. You will guide customers in transforming their operations using our cutting-edge cloud solutions. This role is pivotal in leveraging Google Cloud's secure, scalable, and reliable platform to drive innovation and growth for businesses of all sizes.

This is an opportunity to be part of an entrepreneurial team, shaping the future of how industries utilize technology. You'll play a key part in understanding client needs and translating them into impactful cloud strategies, ensuring they benefit from our advanced technologies.

Lead a high-performing team of AI Customer Engineers and Forward Deployed Engineers, cultivating a culture of excellence and strategic skill development to achieve successful cloud transformations.

Cultivate strong customer partnerships by providing thought leadership in cloud solutions and specialized technical domains, thereby driving significant technical wins.

Collaborate closely with sales teams to shape technical go-to-market strategies and delivery plans, prioritizing advanced workload adoption and the creation of reusable solutions.

Balance technical direction with operational efficiency, conducting reviews and offering insights to drive migration strategies and technical successes. Oversee the development of domain-specific prototypes and proofs-of-concept.

Work across internal Google teams, external partners, and your team to dismantle technical hurdles, providing crucial feedback to Product and Engineering based on real-world application.

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

Possess at least 10 years of experience in cloud-native architecture within a customer-facing or support capacity.

Demonstrate a strong background in AI technologies or concepts.

Exhibit proven experience in leading technical discussions, delivering demos, prototyping, and conducting customer workshops.

Showcase substantial leadership experience, including people management, team leadership, mentorship, or coaching.

Have a track record of driving the adoption of specialized workloads, such as Cloud AI and Data Analytics, with key technical decision-makers.