G

Google

Runs Search and YouTube and builds Gemini AI

Cloud Engineer - Data and AI

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A Bachelor's degree in Computer Science or equivalent practical experience is required.
  • Experience architecting and deploying enterprise-grade cloud data platforms incorporating streaming and batch processing workflows is required.
  • Experience writing software in Python, Scala, R, or a similar language is required.
  • Experience with Gemini models, ADK, Gemini Enterprise, and other Google AI products is required.

Responsibilities

  • Provide expert advisory on architectural frameworks and operational best practices for Agentic platforms, including deployment, monitoring, evaluation, governance, and security protocols.
  • Lead artificial intelligence initiatives through strategic thought leadership, identify agentic workflows, and design architectural solutions for agentic implementations.
  • Deliver big data and machine learning solutions and solve complex technical customer challenges.
  • Identify product features and gaps, guide customers on product challenges, and collaborate with Product Managers and Engineers to influence the Google Cloud Platform roadmap.
  • Provide guidance on architectural data strategies to optimize use across AI models.
  • Deliver best-practice recommendations, tutorials, blog articles, and technical presentations tailored to business and technical stakeholders.
  • Design and implement machine learning solutions for customer use cases using Google products including TensorFlow, DataFlow, and Vertex AI.
  • Work with customers to identify opportunities to apply machine learning in their businesses.
  • Travel to customer sites to deploy solutions and deliver workshops.
  • Work with Product Management and Product Engineering to improve products.
  • Support customer implementation of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, and monitoring.

Desired Qualifications

  • Five years of experience working with recommendation engines, data pipelines, or distributed machine learning is preferred.
  • Experience with data analytics, data visualization techniques and software, and deep learning frameworks is preferred.
  • Experience with core data science techniques is preferred.
  • Knowledge of data warehousing concepts, including technical architectures, infrastructure components, ETL/ELT, and reporting and analytics tools and environments is preferred.
  • Knowledge of cloud computing, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems, and content delivery networks, is preferred.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size
10,001+
Company stage
IPO
Headquarters
Mountain View, CA
Founded
1998

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