AI Engineer Intern

**Role Overview** We are looking for a tech-savvy, curious **AI Engineering Intern** to help manage, optimize, and evolve our AI chatbot ecosystem. While your primary playground will be chatbot, you won’t just be building standard decision-tree bots. You will help us bridge the gap between traditional conversational design and modern AI concepts, working with APIs and Retrieval-Augmented Generation (RAG) to make our bot smarter and more dynamic. This is a hands-on role perfect for someone looking to build a portfolio in real-world AI implementation. **Key Responsibilities** * **Chatbot Engineering \& Management:** Maintain, test, and optimize Dialogflow agents, including intents, entities, and fulfillment. * **RAG \& API Integration:** Implement and tweak RAG frameworks for context-aware responses, and use **Postman** to test webhooks and backend connections. * **Performance Monitoring \& Debugging:** Review chat logs to identify failures, debug conversational flows, and continuously improve user experience. * **Engineering \& Operational Support:** Support full-time engineers with research, prototyping, and project delivery, while assisting with existing operational AI projects. * **Documentation \& Collaboration:** Maintain project documentation, contribute to internal team initiatives, and participate in the full lifecycle of real-time AI projects. **What We Are Looking For (Requirements)** * **The Basics:** Currently pursuing or recently graduated with a degree in Computer Science, Data Science, Information Systems, or a related technical field. * **Dialogflow Exposure:** You’ve built or experimented with Dialogflow (ES or CX) or any other Chatbot in class projects, hackathons, or personal time * **API \& Postman Literate:** You know what a GET/POST request is, you understand JSON formatting, and you are comfortable using Postman to test APIs. * **AI Foundational Knowledge:** You understand the core concepts behind Large Language Models (LLMs) and **RAG** (you know how a bot retrieves data to generate an answer, rather than just guessing). * **Problem Solver:** You don’t mind looking through logs to figure out why a webhook failed. **Nice-to-Haves (Bonus Points)** * Basic coding skills in Python or Node.js (useful for writing fulfillment functions). * Familiarity with vector databases or cloud platforms (Google Cloud, AWS). **What You’ll Learn \& Gain** * Direct mentorship from experienced developers/product managers. * Real-world experience deploying AI features beyond just theoretical prompting. * A standout portfolio piece demonstrating that you can connect modern AI concepts (RAG) with established enterprise tools (Dialogflow).