AI/ML Engineer - LLM & RAG Systems

Description : - Design and build RAG pipelines for rule-based validation - Extract structured rules from PDF/XML/web sources using LLMs - Develop AI workflows using LangChain and LangGraph - Implement semantic search and embeddings for accurate retrieval - Use LangSmith for debugging, tracing, and evaluation - Prototype workflows using LangFlow - Generate explainable AI outputs for artwork validation - Optimize prompts and reduce hallucinations Ideal Candidate : - Strong AI Engineer / LLM Engineer profile with hands-on experience building RAG or LLM applications - Must have 3+ years of software engineering experience with atleast 6+ months in AI/ML, NLP, or deploying LLM based application - Must have strong hands-on experience building RAG pipelines, LLM workflows, semantic search, or AI-powered retrieval systems - Must have hands-on experience with LangChain. Experience with LangGraph, LangSmith, and LangFlow is highly important - Must have worked on embeddings and vector databases like Pinecone, FAISS, Weaviate, ChromaDB, etc. - Strong Python skills with experience building AI/NLP pipelines or backend AI workflows - Must have experience working with unstructured data such as PDFs, HTML, XML, scanned documents, or web data - Must have good understanding of prompt engineering, hallucination reduction, retrieval accuracy, and LLM evaluation - Service or product companies acceptable given they have real AI/ML, LLM based experience - Must be comfortable with a 6-day (3 days in office) hybrid work model. Mon-Friday 8 :30-5 :30 pm and Saturdays 8 :30-1 :00 pm Description : - Design and build RAG pipelines for rule-based validation - Extract structured rules from PDF/XML/web sources using LLMs - Develop AI workflows using LangChain and LangGraph - Implement semantic search and embeddings for accurate retrieval - Use LangSmith for debugging, tracing, and evaluation - Prototype workflows using LangFlow - Generate explainable AI outputs for artwork validation - Optimize prompts and reduce hallucinations Ideal Candidate : - Strong AI Engineer / LLM Engineer profile with hands-on experience building RAG or LLM applications - Must have 3+ years of software engineering experience with atleast 6+ months in AI/ML, NLP, or deploying LLM based application - Must have strong hands-on experience building RAG pipelines, LLM workflows, semantic search, or AI-powered retrieval systems - Must have hands-on experience with LangChain. Experience with LangGraph, LangSmith, and LangFlow is highly important - Must have worked on embeddings and vector databases like Pinecone, FAISS, Weaviate, ChromaDB, etc. - Strong Python skills with experience building AI/NLP pipelines or backend AI workflows - Must have experience working with unstructured data such as PDFs, HTML, XML, scanned documents, or web data - Must have good understanding of prompt engineering, hallucination reduction, retrieval accuracy, and LLM evaluation - Service or product companies acceptable given they have real AI/ML, LLM based experience - Must be comfortable with a 6-day (3 days in office) hybrid work model. Mon-Friday 8 :30-5 :30 pm and Saturdays 8 :30-1 :00 pm