Retrieval-Augmented Generation (RAG) Engineer
Yantran · Chennai · onsite · Posted 36d ago
Undisclosed3–6 yrsfulltimeSourced from
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About this role
Seeking a RAG Engineer to build AI applications that combine enterprise knowledge retrieval with Large Language Models.
Responsibilities:
- Design and develop RAG pipelines.
- Build document ingestion and processing pipelines.
- Implement chunking and embedding strategies.
- Configure vector and hybrid search.
- Integrate LLMs with enterprise knowledge bases.
- Optimize retrieval accuracy.
- Implement reranking and metadata filtering.
- Evaluate RAG performance.
- Develop production APIs and services.
Required Skills:
- RAG.
- LLMs.
- Python.
- Embeddings.
- Vector databases.
- Pinecone/Weaviate/Qdrant/FAISS/Chroma or equivalent.
- Elasticsearch/OpenSearch preferred.
- LangChain/LlamaIndex.
- REST APIs.
- Cloud platforms.
Sourced from naukri
Skills
Retrieval Augmented Generationcloud platformsapiselastic searchFAISSWeaviateVectormetadatavector databasesEmbeddingsOpensearchLarge Language Models (LLMs)PythonPinecone DBLangchainArtificial Intelligence