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Confirmed on the employer's own hiring board on Oct 5, 2026. First seen by Alion on Sep 9, 2026. Google scores B on the Alion truth index.

Overview
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Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

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.

As a Cloud AI Engineer, you'll play a key leadership role in ensuring that strategic customers have the best experience adopting Gemini Enterprise alongside the broader Google Cloud Agentic AI suite of products. You will design and implement robust, production-ready application architectures to support customer use cases, leveraging Gemini Enterprise and core Google AI products. You'll work with customers to identify opportunities to transform their workflows with autonomous agents, actively removing technical barriers to ensure successful deployment and high adoption rates of Gemini Enterprise. You will have access to Google’s technology to monitor application performance, debug and troubleshoot complex agent behaviors, and address customer and partner needs. In this role, you will lead the end-to-end and timely execution of adopting Google Cloud Platform solutions to the customer.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s 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

  • 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.

Qualifications

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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