AI Engineer - RAG & LLM Systems

Role & Responsibilities We are building an AI-powered Artwork Validation Platform that reads global regulatory rules and validates product packaging using LLMs and Retrieval-Augmented Generation (RAG). We are looking for a hands-on AI Engineer with strong expertise in the LangChain ecosystem to design, orchestrate, and optimize intelligent AI workflows. Key Responsibilities: Design and build RAG pipelines for rule-based validationExtract structured rules from PDF/XML/web sources using LLMsDevelop AI workflows using LangChain and LangGraphImplement semantic search and embeddings for accurate retrievalUse LangSmith for debugging, tracing, and evaluationPrototype workflows using LangFlowGenerate explainable AI outputs for artwork validationOptimize prompts and reduce hallucinationsIdeal Candidate Strong AI Engineer / LLM Engineer profile with hands-on experience building RAG or LLM applicationsMandatory (Experience): Must have 3+ years of software engineering experience with atleast 6+ months in AI/ML, NLP, or deploying LLM based applicationMandatory (LLM & RAG): Must have strong hands-on experience building RAG pipelines, LLM workflows, semantic search, or AI-powered retrieval systemsMandatory (LangChain Ecosystem): Must have hands-on experience with LangChain. Experience with LangGraph, LangSmith, and LangFlow is highly importantMandatory (Vector DB & Embeddings): Must have worked on embeddings and vector databases like Pinecone, FAISS, Weaviate, ChromaDB, etc.Mandatory (Programming): Strong Python skills with experience building AI/NLP pipelines or backend AI workflowsMandatory (Data Processing): Must have experience working with unstructured data such as PDFs, HTML, XML, scanned documents, or web dataMandatory (Prompt Engineering): Must have good understanding of prompt engineering, hallucination reduction, retrieval accuracy, and LLM evaluationMandatory (Company): Service or product companies acceptable given they have real AI/ML, LLM based experienceMandatory (Note): 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 pmPreferred (Experience): Exposure to food compliance domain Role & Responsibilities We are building an AI-powered Artwork Validation Platform that reads global regulatory rules and validates product packaging using LLMs and Retrieval-Augmented Generation (RAG). We are looking for a hands-on AI Engineer with strong expertise in the LangChain ecosystem to design, orchestrate, and optimize intelligent AI workflows. Key Responsibilities: Design and build RAG pipelines for rule-based validationExtract structured rules from PDF/XML/web sources using LLMsDevelop AI workflows using LangChain and LangGraphImplement semantic search and embeddings for accurate retrievalUse LangSmith for debugging, tracing, and evaluationPrototype workflows using LangFlowGenerate explainable AI outputs for artwork validationOptimize prompts and reduce hallucinationsIdeal Candidate Strong AI Engineer / LLM Engineer profile with hands-on experience building RAG or LLM applicationsMandatory (Experience): Must have 3+ years of software engineering experience with atleast 6+ months in AI/ML, NLP, or deploying LLM based applicationMandatory (LLM & RAG): Must have strong hands-on experience building RAG pipelines, LLM workflows, semantic search, or AI-powered retrieval systemsMandatory (LangChain Ecosystem): Must have hands-on experience with LangChain. Experience with LangGraph, LangSmith, and LangFlow is highly importantMandatory (Vector DB & Embeddings): Must have worked on embeddings and vector databases like Pinecone, FAISS, Weaviate, ChromaDB, etc.Mandatory (Programming): Strong Python skills with experience building AI/NLP pipelines or backend AI workflowsMandatory (Data Processing): Must have experience working with unstructured data such as PDFs, HTML, XML, scanned documents, or web dataMandatory (Prompt Engineering): Must have good understanding of prompt engineering, hallucination reduction, retrieval accuracy, and LLM evaluationMandatory (Company): Service or product companies acceptable given they have real AI/ML, LLM based experienceMandatory (Note): 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 pmPreferred (Experience): Exposure to food compliance domain