AI Enablement Intern: Agentic Framework (Hybrid)

Electronic Arts

Austin (TX)

Hybrid

USD 34,000 - 48,000

Part time

33 hours ago
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Job summary

Electronic Arts in Austin, Texas is seeking an AI Enablement Intern to join the System Owners team within Fan Care for Summer 2027. You will help scale the Agentic AI Framework to accelerate software delivery and operational workflows.

Collaborate with Architecture, Engineering, QA, Fan Care Operations, and Support to translate needs into backlog items, develop documentation, and measure impact on productivity.

Qualifications

  • Currently enrolled in a Bachelor's degree program with anticipated graduation no earlier than December 2027.
  • Knowledge of Agentic AI architecture and autonomous agent concepts.
  • Familiarity with Agile methodologies and delivering requirements.
  • Interest in enterprise software development lifecycles and IT operations.
  • Strong analytical, collaborative, and communication skills.

Responsibilities

  • Define functional requirements and operating models for an agentic framework.
  • Conduct qualitative research to uncover automation opportunities with cross-functional teams.
  • Translate needs into backlog items for AI agent development.
  • Develop documentation, playbooks, and best-practice guides for adoption.
  • Establish benchmarks to evaluate output accuracy and productivity gains.

Skills

Agentic AI architecture
Functional planning
Agile methodologies
Cross-team collaboration
Enterprise software lifecycles
Problem solving

Education

Bachelor's degree program

Tools

LangChain
OpenAI APIs
Markdown-driven prompts
Jira
Confluence

Job description

Electronic Arts in Austin, Texas is seeking an AI Enablement Intern to join the System Owners team within Fan Care for Summer 2027. You will help scale the Agentic AI Framework to accelerate software delivery and operational workflows.

Collaborate with Architecture, Engineering, QA, Fan Care Operations, and Support to translate needs into backlog items, develop documentation, and measure impact on productivity.

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