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GenAI & Agentic AIPremium
GenAI & Agentic AI Internship
Build production LLM apps and autonomous AI agents with RAG, vector DBs and multi-agent systems.
12 weeks Hybrid Advanced 20 seats Pallavaram, Chennai
Fees on request
Apply before 10 Sept
Tech stack
PythonOpenAI APILangChainRAGVector DBFastAPINext.js
Overview
Work like a real AI engineer. You'll build Generative-AI and agentic applications end-to-end — prompt engineering, retrieval-augmented generation, vector databases, tool-calling agents, agent memory and multi-agent orchestration — culminating in a deployed, evaluated AI product.
What you'll learn
- Generative AI & LLM fundamentals
- Prompt engineering & structured output
- RAG with embeddings + vector databases
- Building tool-calling AI agents
- Agent memory & multi-agent orchestration
- Evaluating & securing AI applications
Learning roadmap
- 1
GenAI foundations & prompt engineering
- LLM basics
- Prompting patterns
- Structured output
- 2
Embeddings & vector databases
- Embeddings
- Chunking
- Vector search
- 3
Retrieval-Augmented Generation
- RAG pipeline
- Grounding
- Evaluation
- 4
AI agents & tool calling
- Agent loop
- Tools
- Function calling
- 5
Agent memory & multi-agent systems
- Short/long memory
- Orchestration
- 6
Capstone: deploy + evaluate + demo
- Deployment
- Guardrails
- Demo day
Real projects you'll build
RAG Knowledge Assistant
A document Q&A assistant grounded in your own data using embeddings + a vector database.
AI Customer Support Agent
A tool-calling agent that resolves tickets, checks orders and escalates intelligently.
Multi-Agent Business Assistant
Coordinated agents (research, writing, analysis) solving a real business task.
Skills you'll gain
LLMsPrompt EngineeringRAGEmbeddingsAI AgentsTool CallingAgent MemoryMulti-Agent SystemsAI EvaluationAI Security
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