Description

You will design and build GenAI and Agentic AI applications for complex document understanding and decision support.

Responsibilities

• Build and optimize RAG pipelines tailored to regulatory and legal documents with high precision.
• Implement document ingestion strategies including contextual chunking, embeddings, and semantic indexing.
• Integrate Knowledge Graphs with LLM workflows using RDF and SPARQL for structured reasoning.
• Orchestrate multi-step AI workflows using LangChain or similar agent frameworks.
• Establish AI QA practices including retrieval evaluation, hallucination detection, and RAGAS-style scoring.

Required Skills

• 5+ years of experience as an AI Engineer focused on LLM-powered solutions.
• Proficiency in Python, GenAI, LLM Development, and RAG architectures.
• Hands-on experience with Agentic AI, NLP, and Embeddings.
• Strong understanding of Knowledge Graphs and LangChain.
• Experience with Docker for containerization.
• BE/B.Tech or equivalent degree.

Preferred Skills

• Experience with legal, regulatory, compliance, and policy documents.
• Familiarity with Java, Kubernetes, and GitOps.
• Knowledge of AI QA evaluation tools like RAGAS and LLM judges.

Key Skills

Education

Any Graduate