Data Science Intern

Role Overview

As a GenAI Engineer, you will design and build production-grade applications leveraging advanced LLM orchestration and RAG architectures to solve complex enterprise challenges.

Responsibilities

• Design and build production-grade GenAI applications using LangChain, LangGraph, and CrewAI
• Implement RAG pipelines with vector databases like Pinecone, Weaviate, or ChromaDB
• Fine-tune and deploy LLMs such as GPT-4, Claude, and Llama
• Build multi-agent orchestration systems for complex workflow automation
• Develop evaluation frameworks to benchmark model performance, latency, and cost

Requirements

• 2+ years working with LLMs, prompt engineering, or NLP in production environments
• Strong Python skills including FastAPI, asyncio, and data pipelines
• Experience with agent frameworks like LangChain, LangGraph, CrewAI, or AutoGen
• Understanding of embedding models, vector search, and retrieval-augmented generation

Nice to Have

• Experience with PyTorch, model fine-tuning, or MLOps tools like MLflow or Weights & Biases

Skills

• Python
• LangChain
• FastAPI
• RAG
• LLMs