Enterprise Artificial Intelligence Intern

EquinixRedwood City, CA

About The Position

Equinix is looking for a visionary AI Engineering Intern to join our Enterprise AI Team. This is not a “shadowing” internship; you will be the primary developer of an Agentic AIs designed to revolutionize how we support our global customers. You will focus on moving beyond simple chatbots to create Autonomous Agents that can navigate Equinix’s internal tools, interpret complex customer data, and execute workflows that drive proactive intelligence.

Requirements

  • Primary developer of an Agentic AIs designed to revolutionize how we support our global customers.
  • Moving beyond simple chatbots to create Autonomous Agents that can navigate Equinix’s internal tools, interpret complex customer data, and execute workflows that drive proactive intelligence.
  • Build Agentic Workflows: Design and deploy AI agents capable of multi-step reasoning, tool-use (function calling), and autonomous problem-solving for our workflows.
  • Bridge the Ecosystem: Enhance our existing Agentic Platforms like Google ADK, Vertex AI.
  • End-to-End Development: Own the full lifecycle, from data ingestion and prompt engineering to RAG (Retrieval-Augmented Generation) implementation and production deployment, and user enablement and adoption.
  • Drive Insight & Intelligence: Develop agents that proactively identify churn risks, summarize complex support tickets, and suggest “next-best-actions” for Customer Success Managers (CSMs).
  • Legacy Modernization: Evaluate existing CS processes and transform them into intelligent, LLM-powered processes.

Responsibilities

  • Design and deploy AI agents capable of multi-step reasoning, tool-use (function calling), and autonomous problem-solving for our workflows.
  • Enhance our existing Agentic Platforms like Google ADK, Vertex AI.
  • Own the full lifecycle, from data ingestion and prompt engineering to RAG (Retrieval-Augmented Generation) implementation and production deployment, and user enablement and adoption.
  • Develop agents that proactively identify churn risks, summarize complex support tickets, and suggest “next-best-actions” for Customer Success Managers (CSMs).
  • Evaluate existing CS processes and transform them into intelligent, LLM-powered processes.
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