Key Responsibilities
- Build AI chatbots integrated with knowledge bases and LLM APIs.
- Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone.
- Develop AI-powered content summarisation and semantic search features.
- Work with embeddings to improve search relevance and information retrieval.
- Optimize prompts and workflows for better LLM performance.
- Collaborate with product and engineering teams to integrate AI solutions into existing platforms.
Required Skills:
- Strong proficiency in Python.
- Experience with FastAPI for building APIs.
- Hands-on experience with one or more LLM APIs such as OpenAI, Claude, Gemini, or similar.
- Good understanding of Prompt Engineering.
- Experience implementing RAG using Pinecone or other vector databases.
- Knowledge of embeddings and semantic search.
- Experience implementing chatbots using knowledge bases and LLM APIs.
Preferred / Exposure To
- LangChain:
- LangGraph:
- MCP (Model Context Protocol):
- AI Agents and Tool/Function Calling
What We Offer
- Collaborative and innovative work environment.
- Career growth opportunities in AI engineering.
- Hands-on experience with modern AI frameworks and production AI systems.
Note: Send your Resume
Let’s get started on building your path to success
Pay: ₹20,000.00 - ₹40,000.00 per month
Perks:
- Leave encashment
- Paid sick time
- Provident Fund
Application Question(s):
- Are you an immediate joiner ?
- What is your current and expected salary ?
- Do you any notice period? If yes mention the period of time