AI & Automation Intern — Legal & People Ops

Teradata

Santa Fe (NM)

On-site

USD 28,000 - 34,000

Full time

2 days ago
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Job summary

Teradata offers a summer internship program of 10–12 weeks, typically May or June through August or September. You will work in a fast-paced, collaborative environment contributing to AI-enabled processes and enterprise automation in Legal and People operations.

You will partner with Legal and People teams, prototype AI solutions, and document adoption materials for scalable implementation, while learning how to manage risk and ensure responsible AI practices.

Qualifications

  • Academic or project experience in AI, data analytics, information systems, CS, or related field.
  • Experience with generative AI tools, prompt design, workflow automation, and low-code/no-code platforms.
  • Strong communication and ability to translate ambiguous problems into actionable steps.
  • Ability to work with confidential information and maintain privacy and security.

Responsibilities

  • Partner with Legal and People teams to document workflows, pain points, data inputs, and desired outcomes.
  • Research and prototype AI-enabled solutions for approved use cases.
  • Build reusable process maps, requirements, test scenarios, and adoption materials.
  • Evaluate outputs for accuracy, privacy, and security; document risks.
  • Support pilots by gathering feedback and reporting impact.

Skills

AI knowledge
Data analytics
Information systems
Legal operations

Education

Pursuing degree (BS/MS)

Tools

Generative AI tools
Prompt design
Workflow automation
Low-code/no-code
Data visualization
Process mapping
User research

Job description

Teradata offers a summer internship program of 10–12 weeks, typically May or June through August or September. You will work in a fast-paced, collaborative environment contributing to AI-enabled processes and enterprise automation in Legal and People operations.

You will partner with Legal and People teams, prototype AI solutions, and document adoption materials for scalable implementation, while learning how to manage risk and ensure responsible AI practices.

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