In this role, you will combine the technical expertise with an ability to lead the execution of enterprise Artificial Intelligence (AI) workloads from proof-of-concept to production. You will be working on Gemini Enterprise engagements to accelerate customer adoption and sustained usage with impact on customer business outcomes and Google Cloud business growth. You will create, manage, and execute the deployment plan, transitioning Gemini Enterprise license agreements into production workloads by providing technical leadership to customers and partners. You will have an impact on the velocity and incremental consumption of customer license agreements, leading to accelerated value realization, higher adoption, and future expansion opportunities.
Responsibilities
- Develop an end-to-end AI deployment plan across customer and partner teams, clearing architectural blockers, and ensuring organizational readiness for launch.
- Execute technical unblocking for key workloads, including writing enterprise grade code, debugging Gemini Enterprise and third-party IT solutions, and architecting end-to-end enterprise AI solutions.
- Drive and track the activation of Gemini Enterprise licenses, moving customers to consumption by executing plans, ensuring quick transitions from basic adoption to advanced AI-assisted workflows.
- Identify opportunities to expand the AI footprint within the account. Spot new use cases such as reasoning tasks or multi-modal agents that drive cross-functional adoption and justify new license agreements.
- Drive sustainable product usage to help customers realize value on an ongoing basis and secure future agreement renewals.
Qualifications
Minimum qualifications:
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 6 years of experience in designing and deploying technical solutions.
- 5 years of experience with cloud native architecture in a customer-facing or support role.
- Experience in deployment planning, orchestration, or change management.
- Experience in programming languages, debugging, or systems design.
- Experience with collaborating and presenting to technical stakeholders or executive leaders.
Preferred qualifications:
- Experience in developing, documenting, and communicating enterprise architecture and end-to-end solutions including multiple technology and organizational domains.
- Experience in one or more of the following: infrastructure modernization, application modernization, data management, data analytics, cloud artificial intelligence, networking, migrations or security.
- Experience in developing applications with AI features, using proprietary or open models and frameworks including prompt and context engineering, and external systems integration.
- Experience in communicating technical concepts to technical and non-technical audiences, including executive stakeholders.
- Ability to prototype concepts and enhance them for production environments.