About Job

Description

We are looking for AI Engineering Interns to join the Cloud Data & AI team and work on real world Artificial Intelligence and Generative AI solutions. The role will involve hands-on development of AI-powered applications, LLM-based solutions, automation, RAG pipelines and agentic AI workflows.

Key Responsibilities:

• Develop AI-powered applications and proof-of-concepts using Python and modern AI frameworks.

• Work with Large Language Models (LLMs) and Generative AI technologies.

• Build and experiment with Retrieval-Augmented Generation (RAG) solutions.

• Develop AI agents and automated workflows using frameworks such as LangChain or LangGraph.

• Integrate LLMs with APIs, databases and enterprise applications.

• Work with embeddings, vector databases and document-processing pipelines.

• Develop prompt engineering and LLM evaluation approaches.Build automation and intelligent workflows using Python and cloud AI services.

• Experiment with models from platforms such as Azure OpenAI, Google Gemini, Snowflake Cortex or similar services.

• Perform testing, debugging and evaluation of AI applications.

• Collaborate with application, data and cloud engineers to build end-to-end AI solutions.

• Follow software engineering practices including Git, modular development, testing and documentation.

Preferred Skills:

• Strong Python programming skills.

• Good understanding of AI/ML fundamentals.

• Understanding of Generative AI and Large Language Models.

• Exposure to prompt engineering, RAG or AI agents.

• Familiarity with LangChain, LangGraph, LlamaIndex or similar frameworks is a plus.

• Exposure to vector databases such as FAISS, Chroma, Pinecone or similar is a plus.

• Basic understanding of APIs, databases and cloud platforms.

• Strong problem-solving and experimentation mindset.Ability to learn new AI technologies quickly.

Ideal Candidate:

A student or recent graduate with strong programming fundamentals and a genuine interest in Generative AI and AI application development. Candidates who have built personal, academic or hackathon projects involving LLMs, RAG, AI agents or AI automation are preferred.