Shopee | Regional Large Language Model (LLM) Agent & Prompt Engineering Intern (Fall 2025/Spring 2026)

Singapore

Intern

03/09 — 17/09/2025

Job Description

To apply for this job, you need to complete both steps below:

STEP 1:
Please click the link to submit your application directly to the company: 

https://www.linkedin.com/jobs/view/4292102679

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STEP 2:
Kindly scroll to the bottom of this page and complete the short VinUni Tracking Form.
Filling out this form alone does not count as applying. Kindly remind this form is not part of the company’s application process. It only helps Careers, Alumni, Industry and Development (CAID) Department discover more opportunities and follow up in case of system issues.

Job Description

  • Proof-of-Concept development: Design and implement workplace-efficiency PoCs on our AI-agent platform.
  • Prompt engineering: Develop, test, and refine prompts to improve model accuracy and usability.
  • Python development: Write clean, maintainable Python code for PoC integrations, tooling, and dashboards.
  • Data structures & algorithms: Apply DSA principles to optimise code performance and model interactions.
  • Reg LLM report automation & generation: Build and maintain automated weekly/monthly performance reports and dashboards for leadership visibility.
  • Data accuracy & insights: validate key metrics, surface insights, and streamline reporting workflows.
  • Collaborate with product owners and end-users for rapid iteration and feedback loops.
  • Provide support on any other tasks assigned by the reporting manager.

 

Requirements

  • Currently pursuing a bachelor’s Degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, or related disciplines.
  • Strong proficiency in Python; familiarity with LLMs, NLP libraries, and prompt-engineering techniques is a plus.
  • Demonstrated understanding of data structures and algorithms (coursework, projects, or competitions).
  • Experience with version control, REST APIs, or basic cloud services is advantageous.
  • Prefer full-time interns; outstanding part-time candidates (≥3 days/week) will be considered

Application form

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