Internship AI Engineer

Job Summary

As an AI Engineer Intern, you will work directly with our software engineering and AI teams to develop real-world AI products deployed to customers. This is a hands-on role focused on building production-ready AI systems rather than purely academic research.

1. AI Agent Development

• System Design: Design, develop, and evaluate AI Agents for transportation and operational workflows.
• Reasoning & Planning: Build Agentic AI systems capable of reasoning, planning, tool usage, and workflow automation.
• Multi-Agent Systems: Develop collaborative multi-agent systems for fleet operations, maintenance intelligence, route planning, and customer support automation.

1. AI Frameworks & Tools

You will leverage a modern AI stack to build scalable solutions:

• Core Languages: Python.
• Orchestration: LangChain, LangGraph.
• Models & Infrastructure: OpenAI APIs, NVIDIA AI Stack.
• Memory & Knowledge: Vector Databases (FAISS, ChromaDB, Milvus) and RAG (Retrieval-Augmented Generation).
• Protocols & Deployment: MCP (Model Context Protocol), Docker, and Cloud Deployment.

1. Product Development

• Integration: Collaborate with software engineers to integrate AI capabilities into production products.
• Feature Engineering: Develop AI-powered features for FMS, TMS, and Predictive Maintenance Platforms.
• Visualization: Build Vision-Language applications and AI-driven Route Planning & Optimization tools.
• Intelligence: Enhance Business Intelligence Dashboards with predictive forecasting.

1. Deployment & Customer-Focused Delivery

• Production Launch: Deploy AI solutions into production environments and monitor real-world performance.
• Continuous Improvement: Monitor, evaluate, and retrain models based on operational data.
• User Feedback: Work closely with customers to translate operational challenges into technical AI solutions.
• Collaboration: Participate in product demonstrations and pilot projects with enterprise clients.

• Production Exposure: Build production-grade AI solutions used by real enterprise customers.
• Cutting-Edge Tech: Deep exposure to Agentic AI, Multimodal AI, and Transportation Intelligence systems.
• Mentorship: Direct guidance from experienced AI researchers and industry practitioners.
• Impact: The opportunity to contribute directly to commercial AI products impacting thousands of vehicles daily.

• Education: Currently pursuing a Master’s or PhD degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field. Bachelor’s students will be considered if they have strong project experience showcasing AI application development.
• Technical Proficiency: Strong familiarity with Python programming.
• AI Foundations: Basic understanding of Machine Learning, LLMs, or Generative AI.
• Soft Skills: Strong problem-solving skills and a passion for building real-world applications with high impact.

• Experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.).
• Hands-on experience with AI Agents, RAG, or Vector Databases.
• Familiarity with web application development, cloud platforms (AWS/GCP/Azure), and containerization (Docker).