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 an AI Outcome Customer Engineer (AI OCE), you will drive initial and ongoing revenue ramp for our enterprise customers, clearing complex blockers and ensuring they realize maximum business value from their Cloud AI investments faster. You will manage and execute the technical deployment plan, transitioning scoped license agreements into robust production deployments by providing authoritative technical leadership to customers and partners.
You will have a direct impact on the velocity and incremental consumption of customer agreements, leading to accelerated value realization, higher adoption, and future expansion opportunities. You will blend sales acumen, enterprise architecture knowledge, technical engagement, and technical delivery management to prove and scale the value of Google's premier Cloud AI 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.
Responsibilities
- Develop and orchestrate a structured, end-to-end technical deployment plan across customer and partner teams. Lead upfront architectural validation to ensure integration readiness before execution begins.
- Dive into complex technical workflows to diagnose, debug, and resolve implementation roadblocks. Act as a technical bridge to core product and support engineering teams to eliminate systemic friction and accelerate customer delivery.
- Drive and track the progress of the initial and ongoing ramp of Cloud AI license agreements, guiding enterprise workloads from agreement to active consumption as rapidly and securely as possible.
- Partner collaboratively with Account an CEs team during the technical evaluation phase of key deals to ensure proposed Cloud AI solutions are architected for viable, scalable long-term adoption.
- Drive sustainable, secure Cloud AI product usage to help customers continuously realize quantifiable business outcomes and secure future contract renewals.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 6 years of experience with cloud-native architecture in technical delivery, customer engineering, or enterprise architecture and in a customer-facing or enterprise support role.
- Experience in technical deployment planning, architecture orchestration, or technical delivery management.
- Experience with enterprise integrations (APIs, ECMs, identity), Cloud infrastructure, and AI/ML model deployments.
- Experience with programming languages, API integration, debugging, or enterprise systems design.
- Experience leading technical delivery strategies, debugging systems, and interfacing with product/engineering organizations.
Preferred qualifications:
- L300/L400 level technical proficiency or relevant AI/ML and Cloud architecture certifications.
- Experience guiding customers through the architectural and organizational transformations needed to deploy production-grade AI models or agents in enterprise environments.
- Technical experience in one or more of the following: Cloud AI solutions, Enterprise Data Management, Data Analytics, Infrastructure Modernization, Security, or Cloud Networking.
- Ability to dive deep into novel technical problems, decipher extreme ambiguity, diagnose bugs, and emerge with credible architectural solution.
- Proven track record interfacing directly with core product and engineering organizations to escalate product bugs, advocate for feature gaps, and unblock systemic deployments.