Customer Engineering Manager, AI, Manufacturing and Conglomerates, Google Cloud

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As a Practice Customer Engineering (CE) Manager, you lead and deploy a team of subject matter experts responsible for working alongside our customers to provide trusted technical and solution advice to accelerate workload migration and remove technical blockers. You will foster a culture of technical excellence and understand the mechanics of architecture, delivery, and consumption within your specialized domain and Google Cloud’s products and solutions.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

• Lead a team of AI Customer Engineers and Forward Deployed Engineers, focusing on team culture, talent strategy, and skills development to deliver successful cloud transformations for customers and accelerate value realization.
• Foster customer partnership and provide thought leadership related to cloud, transformation, and highly specialized technical solutions in your Practice to drive technical wins.
• Partner with Sales to define technical go-to-market strategies and delivery plans, focusing on advanced workload adoption and repeatable solution development.
• Balance technical leadership with operational excellence; lead workload and opportunity review meetings and provide insight into how to achieve technical wins and migration strategy, working directly with customers, partners, and prospects. Oversee domain-specific prototyping and proofs-of-concept.
• Work cross-functionally across Google, partners, and your team to resolve technical roadblocks, and provide critical feedback loops to Product and Engineering based on field experience.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer-facing or support role.
• Experience with AI technologies or concepts.
• Experience with technical conversations, demos, prototyping, or workshops with customers.
• Experience in leadership (e.g., people management, team lead, mentorship, coaching).
• Experience driving the adoption of specialized workloads (e.g., Cloud AI, Data Analytics) with technical decision makers.

Preferred qualifications:

• Experience influencing cross-functional teams (e.g., Product Management, Engineering, Sales, Marketing, Partner), customers, and partners to impact business goals, customer experience, and customer expansion.
• Experience as a pre-sales manager or technical customer-facing people manager within a professional services or sales engineering team.
• Experience tailoring and delivering compelling messages by audience, asking strategic questions, and leading conversations that accelerate value realization and business opportunity.

• Bachelor's degree or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer-facing or support role.
• Experience with AI technologies or concepts.
• Experience with technical conversations, demos, prototyping, or workshops with customers.
• Experience in leadership (e.g., people management, team lead, mentorship, coaching).
• Experience driving the adoption of specialized workloads (e.g., Cloud AI, Data Analytics) with technical decision makers.