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About the Role

We are looking for a hands-on AI Engineer to build and scale an AI-powered legal analysis platform. You will work on cutting-edge applications of NLP, Generative AI, and AI agents to analyze complex legal documents and generate structured insights.

This role requires strong experience in LLMs, RAG, embeddings, and agent-based workflows, along with the ability to build production-grade AI systems end-to-end. You will be a core contributor to a platform that transforms how legal professionals interact with documents — moving from manual review to intelligent, automated analysis.

Key Responsibilities

▸ Design and build AI pipelines for document analysis, including parsing, extraction, and summarization

▸ Develop RAG (Retrieval-Augmented Generation) systems using vector databases for semantic legal search

▸ Build and manage AI agents (LangGraph / LangChain) for multi-step reasoning and legal inference workflows

▸ Implement structured data extraction from documents using JSON outputs and schema-driven extraction

▸ Optimize prompts, embeddings, and retrieval strategies for accuracy, reliability, and performance at scale

▸ Integrate AI services with backend systems including APIs, databases, and cloud storage

▸ Build scalable, asynchronous processing pipelines using Kafka / RabbitMQ / SQS for high-volume document ingestion





▸ Ensure high-quality AI outputs through evaluation frameworks, benchmarks, and continuous improvement loops

Required Skills

Core AI & ML Expertise

▸ Solid hands-on experience with Python for AI/ML engineering and system development

▸ Proven experience working with LLMs including OpenAI, Claude (Anthropic), Gemini, or similar models

▸ Deep experience building production RAG pipelines and semantic search systems

▸ Solid understanding of embeddings, chunking strategies, and vector databases (pgvector, Pinecone, Weaviate, Chroma, etc.)

▸ Experience with AI agent frameworks such as LangGraph, LangChain, or equivalent orchestration tools

▸ Experience with PostgreSQL and relational data modeling for AI application backends

▸ Familiarity with event-driven and asynchronous systems (Kafka, RabbitMQ, AWS SQS, or similar)

▸ Experience building and deploying production-grade REST APIs (FastAPI strongly preferred)

Nice to Have

Skill / Experience

Context

Legal-Tech, FinTech, or Document-Heavy Domains

Understanding of compliance, contracts, or regulatory documents

OCR & Document Processing

PDF parsing, AWS Textract, Azure Form Recognizer, or similar tools

AWS Cloud Services

S3, Lambda, ECS/EKS for containerized AI workload deployment

Security & Data Privacy

PII detection, handling, and anonymization in AI pipelines

Apply on Kit Job: kitjob.in/job/446ok7

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