Data Scientist

Overview

We are looking for a Senior AI Engineer / Data Scientist to build and deploy enterprise-grade AI and GenAI solutions across document intelligence, conversational AI, financial analytics, and computer vision use cases. The role requires strong hands-on expertise in LLM orchestration, RAG pipelines, and cloud-native deployments.

Job Description

Key Responsibilities

Design and develop end-to-end AI solutions including Document AI, Enterprise LLM, and Text-to-SQL systems

Build and orchestrate LLM workflows using LangChain and LangGraph

Develop document classification, extraction, validation, and compliance pipelines

Implement Business Rule Engines (BRE) for business and regulatory logic

Build conversational AI systems with contextual memory and follow-up handling

Develop and optimize RAG pipelines using vector and graph databases

Fine-tune and evaluate computer vision and transformer-based models

Deploy and scale AI workloads on cloud platforms

Collaborate with product, data, and business teams to deliver production-ready AI systems

Mandatory Skills

Strong proficiency in Python (Pandas, NumPy, etc.)

Hands-on experience with LangChain / LangGraph

Experience in Document AI / OCR / NLP / LLM-based systems

Cloud expertise in at least one: GCP (Vertex AI) OR Azure (Azure AI Foundry) (mandatory)

Experience with SQL and NoSQL databases

Good to Have

Experience with RAG architectures, PGVector / FAISS, or Neo4j

Exposure to computer vision models (YOLO, LayoutLM, PyTorch)

Experience in BFSI, compliance, or enterprise document workflows

Education

Tier-1 or Tier-2 college preferred (IITs, NITs, IIITs, or equivalent reputed institutions)

Master’s or Bachelor’s degree in Computer Science, AI, Data Science, or related fields

What We Offer

Work on cutting-edge GenAI and LLM platforms

High-ownership role with end-to-end responsibility

Opportunity to build scalable AI solutions for enterprise clients

Skills & Requirements

Python, Pandas, NumPy, LangChain, LangGraph, LLM orchestration, RAG pipelines, Document AI, OCR, NLP, Large Language Models (LLMs), GCP Vertex AI, Azure AI Foundry, SQL, NoSQL, Vector Databases, PGVector, FAISS, Neo4j, Business Rule Engine (BRE), Conversational AI, Text-to-SQL, Computer Vision, YOLO, LayoutLM, PyTorch, Cloud Deployment, CI/CD, Enterprise AI Systems

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