Cloud AI Engineer, Technical Onboarding Center

About the job:
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.

Responsibilities:
Lead the delivery, deployment, and implementation of Gemini Enterprise solutions, utilizing Agent Development Kits (ADKs) to solve complex, enterprise-scale technical customer challenges.
Act as a trusted technical advisor to Google’s most strategic customers to shape their AI strategy, drive, and accelerate the adoption of Gemini Enterprise.
Provide architectural guidance on existing product challenges, collaborate closely with the engineering team to address gaps, and architect scalable workarounds for edge cases.
Deliver leading practice recommendations and technical presentations adapted to different levels of key business and technical stakeholders (including C-suite executives) to proactively foster Gemini Enterprise adoption and enablement.

Minimum qualifications:
Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
3 years of experience in software engineering, cloud architecture, or technical consulting, infrastructure with 2 years of experience in building and deploying GenAI applications, intelligent agents, or LLM-powered solutions to production.
Experience building and orchestrating agents using ADKs, LangChain, LlamaIndex, AutoGen and in designing modern application architectures, including API design, microservices, and integrating AI models into existing enterprise software systems.
Experience with Python.

Preferred qualifications:
Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Google Cloud Professional certifications.
Experience implementing scalable RAG architectures and securely connecting LLMs with external productivity tools (e.g., Google Workspace) and complex enterprise databases in high-traffic environments.
Experience leading technical project deployments, working with engineering teams, or acting as the technical lead on large-scale cloud transformations.
Experience deploying, configuring, and managing enterprise-grade generative AI platforms (particularly Gemini Enterprise), with an understanding of AI security, Large Language Models (LLM) governance, guardrails, and enterprise compliance requirements (e.g., data privacy regulations).