AI Intern

Company Name : BRAINWONDERS
Experience: 0 1 Year & Freshers / 2026 Pass-outs can apply)
Location: Churchgate
Type: Internship 6 months | Possibility of Full-time

Focus Areas:
-- Large Language Models (LLMs)
-- Agentic AI & Autonomous Systems
-- Multi-Agent Systems & Agent Orchestration
-- ML Fundamentals & Transformers
-- RAG, Embeddings & Vector Databases
-- Cloud Deployment & Scaling on AWS

Responsibilities
Build and test LLM-powered applications, AI agents, and autonomous workflows.
Design and implement agentic AI systems capable of planning, reasoning, tool use, and task execution.
Develop multi-agent systems where multiple specialized agents collaborate to solve complex tasks.
Experiment with agent frameworks such as LangGraph, CrewAI, LangChain, and other emerging agentic AI frameworks.
Implement agent memory, state management, task decomposition, planning, routing, and orchestration.
Integrate agents with external tools, APIs, databases, search systems, and other services using function/tool calling.
Explore Model Context Protocol (MCP) and other approaches for connecting AI agents with external tools and data sources.
Use and adapt transformer-based models such as LLaMA, Mistral, and other open-source or proprietary LLMs for domain-specific applications.
Build RAG pipelines using embeddings and vector databases for knowledge retrieval and contextual reasoning.
Deploy AI models, agents, and supporting services on AWS (Lambda, EC2, S3, SageMaker, etc.).
Work on prompt engineering, structured outputs, fine-tuning, model selection, and pipeline optimization.
Develop evaluation strategies to measure agent accuracy, reliability, latency, cost, and task completion.
Implement monitoring, logging, and debugging for LLM and agentic workflows.
Collaborate with the team to prototype and productionize AI copilots, autonomous workflows, and intelligent automation systems.

Requirements :
Strong understanding of LLMs, tokenization, transformers, embeddings, and generative AI fundamentals. Good Python programming skills.
Familiarity with tools/libraries such as Pandas, NumPy, Hugging Face, LangChain, LangGraph, or CrewAI. Understanding of AI agent concepts, including tool calling, planning, reasoning, memory, state, and orchestration.
Basic understanding of multi-agent architectures and how multiple agents can collaborate or delegate tasks.
Familiarity with RAG, vector databases, semantic search, and embeddings.
Exposure to AWS services such as EC2, Lambda, S3,
Basic knowledge of machine learning and hands-on project experience.
Ability to build and debug end-to-end AI applications.
Strong curiosity and willingness to experiment with rapidly evolving agentic AI technologies.

Good to Have
Hands-on experience building an AI agent or multi-agent system.
Experience with LangGraph, CrewAI, AutoGen, or similar agent frameworks.
Experience implementing tool/function calling and agent API integrations.
Familiarity with MCP (Model Context Protocol).
Experience with agent memory, state management, planning, routing, and workflow orchestration.
Experience with Docker
Experience evaluating LLMs or agents using automated evaluation frameworks.
Contributions to open-source AI tools, models, agents, or frameworks.
Personal projects involving LLMs, RAG, AI agents, or multi-agent systems

I nternship Details
Location: Churchgate
Working Days: Monday to Saturday
Working Hours: 10:00 AM 7:00 PM
Duration: 6 Months Stipend: 10-25k per month ( Based upon skillset)

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.