Prompt Engineering Intern

About the Role

We are looking for a Prompt Engineering Intern to build reliable, reusable AI prompt systems, templates, and automated workflows across content, curriculum, design, and operations at INFINEO. You will work on designing structured prompt architectures, benchmarking performance across leading AI models (ChatGPT, Claude, Gemini), evaluating edge cases, and building repeatable AI workflows that elevate company-wide operational efficiency.

Key Responsibilities

• Build structured, reusable prompt templates and system instructions for team workflows across departments
• Test, benchmark, and optimize prompt performance across major Large Language Models (ChatGPT, Claude, Gemini)
• Refine prompt logic, system rules, and output formatting based on response quality, edge cases, and user feedback
• Maintain organized internal prompt libraries and write clear documentation for team deployment
• Standardize AI-assisted workflows across content creation, curriculum design, visual generation, and operations
• Research emerging prompt engineering techniques, model capabilities, and AI automation tools

Requirements & Tech Stack

• High curiosity about Artificial Intelligence models, LLM behaviors, and prompt mechanics
• Strong logical, structured thinking and first-principles problem-solving skills
• Rapid experimentation mindset with sharp attention to detail and output quality
• Comfort working with major AI interfaces, system prompts, and structured data formats
• Ability to document technical workflows clearly and work independently

Good to Have

• Hands-on experience working with ChatGPT, Claude, Gemini, or similar Large Language Models
• Understanding of prompt engineering techniques (e.g., system instructions, few-shot prompting, chain-of-thought, XML tag structuring)
• Interest in process automation, workflow optimization, and technical documentation
• Basic familiarity with API integrations, Python, or AI automation platforms

What You'll Get

• Certificate of Internship
• Letter of Recommendation (LOR), based on performance
• LinkedIn Recommendation, based on performance
• Practical hands-on experience building enterprise AI workflows and prompt systems for real EdTech products
• Broad exposure to applied prompt engineering across content, design, curriculum, and startup operations
• Opportunity to shape AI adoption across core company initiatives
• High-performing interns may be considered for future full-time opportunities based on performance and business requirements