AI Engineer - RAG & LLM Systems

Roles & 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 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 :

- Mandatory (Experience) : Must have 3+ years of software engineering experience with atleast 6+ months in AI/ML, NLP, or deploying LLM based application

- Mandatory (LLM & RAG) : Must have strong hands-on experience building RAG pipelines, LLM workflows, semantic search, or AI-powered retrieval systems

- Mandatory (LangChain Ecosystem) : Must have hands-on experience with LangChain. Experience with LangGraph, LangSmith, and LangFlow is highly important

- Mandatory (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 workflows

- Mandatory (Data Processing) : Must have experience working with unstructured data such as PDFs, HTML, XML, scanned documents, or web data

- Mandatory (Prompt Engineering) : Must have good understanding of prompt engineering, hallucination reduction, retrieval accuracy, and LLM evaluation

- Mandatory (Company) : Service or product companies acceptable given they have real AI/ML, LLM based experience

- Mandatory (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 pm

- Preferred (Experience) : Exposure to food compliance domain