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Cloud Engineer, Data and AI

Google
Gurugram, IND
Mid · 5+ years experience
Onsite
Discovered 1 weeks ago
geminipythonscala

Full Job Posting

Responsibilities

  • Provide expert advisory on architectural frameworks and operational best practices for comprehensive Agentic platforms, encompassing deployment, monitoring, evaluation, governance, and security protocols.
  • Lead comprehensive artificial intelligence initiatives through strategic thought leadership, while identifying agentic workflows and designing robust architectural solutions for advanced agentic implementations.
  • Deliver effective big data and machine learning solutions and solve complex technical customer challenges.
  • Identify new product features and feature gaps, provide guidance on existing product challenges, and collaborate with Product Managers and Engineers to influence the roadmap of Google Cloud Platform.
  • Provide expert guidance on architectural data strategies to ensure optimized utilization across different AI models. Deliver best practices recommendations, tutorials, blog articles, and technical presentations adapting to different levels of key business and technical stakeholders.

Minimum qualifications:

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

Preferred qualifications:

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

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