Customer Engineer, SLED, Educational Institution
- Location
- Ohio, USA
- Work model
- On-Site
- Level
- Staff
- Salary
- $152k – $221k/yr
- H-1B history
- 2,460 approvals (FY2023)
- Posted
- 2h ago
Skills
About this role
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 Customer Engineer, you will partner with technical Sales teams to differentiate Google Cloud and our unique Google Public Sector offerings for Educational Institution and initiatives as assigned. You will empower the institutions to harness the full potential of the Google ecosystem by designing creative, agentic AI solutions that solve institutional issues. Moving beyond traditional data life-cycles, you will guide proofs of concept and guide technical strategy to build proactive, self-sustaining AI agents and intelligent data ecosystems that transform the student, researcher, and administrative experience. Leveraging your technical experience and presentation skills, you will engage with educational leaders to translate their academic goals into highly automated and practical architectures tailored for the public sector. Bringing technical, communication, and organizational skills, you will join a team of fellow Googlers dedicated to mutual respect and equal opportunities for success. Located in close proximity to Columbus, Ohio Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $152000 - $221000 (USD) + 42.86% bonus target + equity + benefits Learn more about benefits at Google .
Collaborate with the Sales team to uncover and qualify Google Cloud and AI-first opportunities, address technical objections around adoption, and developing strategic pathways to clear technical blockers. Own the technical relationship with stakeholders at Educational Institution, leading product briefings on Google Cloud and and Google's GenAI portfolio, manage innovative, agentic proof-of-concept (PoC) work, and orchestrating specialized technical resources across Google Public Sector. Demonstrate and prototype intelligent integrations, bringing autonomous agents and AI-powered workflows to life directly within complex environments. Design and recommend AI-optimized enterprise architectures and integration strategies, laying the secure platform and data infrastructure foundations required to successfully deploy comprehensive, forward-looking solutions. Sit onsite 2-3 days a week and travel to industry conferences and related events as required to engage directly with educational leaders.
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 cloud engineering, on-premise engineering, virtualization, or containerization platforms. Experience working as a Technical Sales Engineer in a cloud computing environment, or equivalent experience in a customer or partner-facing role. Experience migrating legacy applications to cloud platforms, and establishing data structures for machine learning