GenAI Intern

Role Overview

We are looking for a GenAI Intern with strong experience in LLM-based systems, Retrieval-Augmented Generation (RAG) and structured data integration. The ideal candidate has hands-on experience building production-grade AI chatbots that combine LLMs, databases, vector stores and guardrails, especially in healthcare or sensitive data environments. You will work on developing and fine-tuning advanced AI models, exploring GenAI, LLMs, and Deep Learning applications.

Responsibilities

• Design and build LLM-powered chatbots using structured (SQL/NoSQL) and unstructured data.
• Implement intent classification, guardrails and safe response generation.
• Build hybrid AI pipelines combining Databases (MySQL/PostgreSQL), Vector databases (Qdrant, Pinecone, Weaviate), and LLMs (OpenAI, LLaMA, Mistral).
• Ensure accurate, deterministic handling of factual queries.
• Implement RAG pipelines for summarization and semantic retrieval.
• Debug hallucination, incorrect counts, and reasoning failures in LLM outputs.
• Implement observability, logging, evaluation, and regression testing for GenAI systems.
• Collaborate with backend, frontend, and product teams.

Requirements

• Strong experience with LLMs (LLaMA, Mistral, Claude, etc.).
• Expertise in prompt engineering for system prompts, intent classification, and tool/function calling.
• Hands-on experience with RAG architectures and embedding models.
• Experience with vector databases like Qdrant, Pinecone, Weaviate, or FAISS.
• Strong backend experience with Python and Flask / FastAPI.
• Working knowledge of SQL (MySQL/PostgreSQL).
• Availability for a 6-month internship.
• Completed projects in GenAI, LLM, Langchain, AI and NLP.

Skills

• Python
• LLM
• RAG
• LangChain
• SQL

Nice to Have

• Knowledge graphs (Neo4j, RDF, etc.).
• LLM evaluation frameworks.
• Multi-agent systems.
• CI/CD for AI systems, DevOps.
• Model observability & monitoring.

Benefits

• Stipend - INR 5K-10K.
• Certificate & Letter of Recommendation upon completion.
• Flexible Work Hours.
• Exposure to Cutting-Edge AI Technologies.
• Collaborative Learning Environment.