Lead Data Scientist (Agentic AI & RAG)

Careernet; Hyderabad; On-site; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Deep Learning experience

Generative AI exposure

Job summary

Careernet is seeking a senior Data Scientist to design and build AI agents and multi-agent systems. You will productionize LLM apps using RAG architectures, and develop ML models for diverse tasks including NLP, forecasting, and anomaly detection.

The role requires 6–7 years in Data Science/ML, strong statistical background, and hands-on experience with end-to-end ML pipelines and enterprise-grade AI solutions.

Qualifications

• 6-7 years of experience in Data Science and ML.
• End-to-end ML solution development.
• NLP and LLM development for semantic understanding.
• RAG architectures and enterprise LLM applications.
• Statistical methods and experimental design including A/B testing.

Responsibilities

• Design and develop AI agents and multi-agent systems.
• Build and productionize LLM applications using RAG architectures.
• Develop ML models for classification, regression, forecasting, recommendations, anomaly detection.
• Implement NLP solutions such as text classification, entity extraction, semantic search, conversational AI, sentiment analysis.
• Apply statistical modeling and experimental design to validate model performance and drive decisions.

Skills

Agentic AI

LLM development

NLP

RAG

Deep Learning

Education

Master's or PhD in Computer Science, Statistics, Mathematics

Tools

LangGraph

LangChain

Semantic Kernel

Python

RAG pipelines

Job description

Key Skills

Agentic AI, LLM, AI/ML, Data Scientist, Statistical Analysis, NLP, Retrieval-Augmented Generation (RAG), Semantic AI, Generative AI, Deep Learning

Roles and Responsibilities

• Design and develop AI agents and multi-agent systems using LangGraph, LangChain, and Semantic Kernel.
• Build and productionize LLM applications using RAG architectures, including retrieval pipelines and ranking strategies.
• Develop machine learning models for classification, regression, forecasting, recommendations, and anomaly detection.
• Implement NLP solutions such as text classification, entity extraction, semantic search, conversational AI, and sentiment analysis.
• Apply statistical modeling and experimental design to validate model performance and drive data-driven decisions.

Skills Required

• 6-7 years of experience in Data Science and Machine Learning
• Data Science and end-to-end ML solution development
• Statistical Analysis (probability, hypothesis testing, regression analysis, Bayesian statistics, A/B testing)
• NLP and LLM development for semantic understanding and language tasks
• Agentic AI and RAG (retrieval-augmented generation) for enterprise LLM applications

Good to Have

• Deep Learning and Generative AI experience
• Semantic AI experience

Education

Master's or PhD in Computer Science, Statistics, Mathematics, or a related field (or equivalent practical experience)