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Mid-level LLM/GenAI role in Bangalore with popular skills and metro location increases competition.
Role requires specialized LLM, RAG, and regulatory-compliance expertise, limiting cross-industry transferability.
Explicit 4–8 years plus many mandatory LLM, RAG, LangChain, and compliance skills create strict filters.
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Design and implement GenAI and Agentic AI applications focused on complex document understanding, reasoning, and decision support in legal and regulatory domains.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines and document ingestion strategies tailored to compliance and policy documents ensuring high precision and grounded responses.
Develop and maintain mechanisms for reference identification, citation tracking, traceability, and AI quality assurance including hallucination detection and evaluation within regulated environments.
4-8 years of experience as an AI Engineer specializing in LLM-powered solutions for legal, regulatory, and compliance document workflows.
Mandatory skills include strong hands-on expertise in Python (primary), NLP/NLU, GenAI/LLM application development, RAG, embeddings, contextual chunking, Knowledge Graphs (RDF), SPARQL, LangChain or LangGraph, Docker, Git, and AI quality assurance methods (e.g., RAGAS, LLM judges).
Educational qualification: BE/B.Tech or Equivalent Degree.
Work Experience Required: 4-8 Years.
Experience specifically with AI applications for legal, regulatory, compliance, and policy document workflows with attention to auditability, explainability, and risk controls.
Skilled in designing multi-step AI workflows using agent frameworks like LangChain or LangGraph and proficient in integrating Knowledge Graphs for structured and unstructured reasoning.
Comfortable managing end-to-end model lifecycle activities including experimentation, versioning, deployment readiness, and monitoring handover in regulated environments.