Responsibilities
- Build autonomous AI agents using LangChain, LangGraph, and similar frameworks.
- Develop RAG pipelines with vector DBs like FAISS, Pinecone, or ChromaDB.
- Create FastAPI endpoints to expose agent functionality.
- Implement Model Context Protocol (MCP) for tool-agent integrations.
- Optimise prompts, workflows, and retrieval strategies for real performance.
- Contribute to new agentic AI design patterns and innovations.
Requirements
- We're looking for engineers with AI/ML Projects Exposure (Beginner to Advanced).
- Proficient in Python, with a strong track record of AI/ML experiments or projects.
- Familiar with one or more of these: LangChain/LangGraph, HuggingFace, PyTorch/TensorFlow, RAG pipelines.
- Able to build and showcase working prototypes or production-ready components.
- Curious, hands-on builders who want to grow in GenAI, LLMs, and agent-based systems.
Bonus Points If You've Worked On
- LLM fine-tuning (LoRA, QLoRA), memory systems.
- AutoGen, CrewAI, MCP, or other agent frameworks.
- Docker, async programming, API integrations.
This job was posted by S M Nandakishore from CAW Studios.
