LabelBlind®️
Website:
labelblind.com
Job details:
AI Engineer – RAG & LLM Systems
Location: In Office / Hybrid
Experience: 3–7 Years
About the Role:
Company Description
LabelBlind® Digital Solutions revolutionizes the food industry by offering comprehensive tools for Product and Labelling Compliance, Nutrition Assessment, Labelling Automation, and Market Readiness for food companies. Through its flagship product, FoLSol®️, LabelBlind® delivers India’s first digital food labelling solution designed to ensure regulatory compliance, transparency, accuracy, and efficiency in creating food labels.
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
Required Skills:
- Strong experience with LLMs and RAG systems
- Hands-on expertise in LangChain, LangGraph, LangSmith, LangFlow
- Experience with embeddings and vector databases (FAISS, Pinecone, Weaviate)
- Proficiency in Python and NLP pipelines
- Experience with unstructured data (PDF, HTML, XML)
- Strong understanding of prompt engineering and evaluation
Good to Have:
- Experience in compliance or regulatory domain (Food labeling preferred)
- Exposure to OCR tools (Tesseract, AWS Textract, Google Vision)
- Knowledge of fine-tuning or domain-specific embeddings
Success Metrics:
- High accuracy in rule extraction and validation
- Improved retrieval precision and reduced hallucinations
- Clear traceability (rule → source → reasoning)
Click on Apply to know more.