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Hiring for GenAI Intern

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. As GenAI Intern, you will work on developing and fine-tuning advanced AI models, exploring GenAI, LLMs, Deep Learning applications. You will gain hands-on experience with state-of-the-art AI tools and frameworks while working alongside experienced AI professionals.

Location: Pune, India

Key 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 or equivalents)
• Vector databases (Qdrant, Pinecone, Weaviate, etc.)
• LLMs (OpenAI, LLaMA, Mistral, etc.)
• Ensure accurate, deterministic handling of factual queries (counts, dates, records)
• Implement RAG pipelines for summarization and semantic retrieval (not for factual counting)
• Design non-SQL abstractions (API layers, event indexes, knowledge graphs when needed)
• 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
• Explain technical decisions clearly to non-AI stakeholders

Required Technical SkillsCore GenAI & LLM

• Strong experience with LLMs (LLaMA, Mistral, Claude, etc.)
• Prompt engineering for:
• System prompts
• Intent classification
• Tool/function calling
• Safety & refusal handling
• Understanding of LLM limitations (hallucinations, counting errors, reasoning limits)

RAG & Embeddings

• Hands-on experience with RAG architectures
• Embedding models (e.g., BGE, E5, OpenAI embeddings)
• Vector databases:
• Qdrant (preferred)
• Pinecone / Weaviate / FAISS
• Ability to decide when NOT to use vector search

Backend & Data

• Strong backend experience with Python
• Experience with Flask / FastAPI
• Working knowledge of:
• SQL (MySQL/PostgreSQL) OR structured alternatives
• Data modeling for event-based systems
• Experience building API layers over data sources

System Design

• Intent-based routing (COUNT, HISTORY, SUMMARY, OUT_OF_SCOPE, etc.)
• Guardrails, policy enforcement and validation layers
• Caching, performance optimization and scalability.

Who Can Apply?

We are looking for candidates who:
✅ Are available for a 6-month internship.
✅ Have completed projects in GenAI, LLM, Langchain, AI and NLP
✅ Have a strong understanding of LLMs, Transformers, NLP
✅ Are proficient in Python, SQL
✅ Are passionate about AI and eager to learn and innovate.

Perks & Benefits:

• Stipend - INR 5K-10K
• Certificate & Letter of Recommendation upon completion.
• Flexible Work Hours – Work at your convenience.
• Exposure to Cutting-Edge AI Technologies.
• Collaborative Learning Environment with industry experts.

Nice-to-Have (Bonus Skills)

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

What We Value Most

• Ability to debug and explain failures
• Ownership mindset
• Clear thinking over hype
• Knowing when not to use LLMs
• Strong fundamentals in data & system design

Experience Level : you must have good experience for hands-on with GenAI / LLM systems

How to Apply? :
If you are interested in this exciting opportunity, send your resume to teams.aiindia@gmail.com with the subject line "Application for GenAI Internship – Ai India". with (Optional) GitHub / blog / architecture diagrams. Thank you!

Job Type: Internship

Pay: ₹5,000.00 - ₹15,000.00 per month

Application Question(s):

• Which of the following AI frameworks have you used?

TensorFlow
PyTorch
Hugging Face Transformers
LangChain
OpenCV
YOLO

• Do you have experience working with Generative AI models?
• Have you worked on projects involving Deep Learning and Computer Vision?

Work Location: In person