17:I[832,["6669","static/chunks/app/(Engagement)/similar-jobs/%5Bid%5D/page-1d33e7066d10f3de.js"],"default"] 19:I[5878,["6669","static/chunks/app/(Engagement)/similar-jobs/%5Bid%5D/page-1d33e7066d10f3de.js"],"Image"] 18:T613,

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

Regional Large Language Model (LLM) Agent & Prompt Engineering Intern (Spring 2027)