Cloud AI Engineer (English)
Bengaluru, Karnataka, Indiaonsitefull timeToday
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:
Deliver, deploy, and implement Gemini Enterprise solutions, utilizing Agent Development Kits (ADKs) to solve complex technical customer challenges.
Act as a trusted technical advisor to Google’s most strategic customers to drive and accelerate the adoption of Gemini Enterprise.
Provide guidance on existing product challenges, and collaborate with the engineering team to address the challenges or provide possible workarounds.
Deliver leading practice recommendation and technical presentations adapted to different levels of key business and technical stakeholders 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.
Experience building generative AI applications, intelligent agents, or LLM-powered solutions, and working directly with technical customers.
Ability to communicate in English fluently to support client relationship management.
Preferred qualifications:
Experience building and orchestrating agents using Agent Development Kits (ADKs) or popular frameworks (e.g., LangChain, LlamaIndex, AutoGen).
Experience implementing Retrieval-Augmented Generation (RAG) architectures and securely connecting LLMs with external productivity tools (e.g., Google Workspace) and internal databases.
Experience in leveraging LLMs to deploy multimodal solutions encompassing text, image, video, and voice.
Experience deploying, configuring, and managing enterprise-grade generative AI platforms, particularly Gemini Enterprise, with an understanding of security, governance, and compliance requirements.
Knowledge of cloud computing, including serverless execution environments, virtualization, hosted services, multi-tenant cloud infrastructures, and secure cloud networking.
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