Senior Data Scientist_GenAI (LLM, RAG, LangGraph) - Immediate Joiners

Role Overview :

We are seeking a highly skilled

Senior Data Scientist

with hands-on experience in

Generative AI

to design, build, and deploy advanced AI solutions. This role involves working on cutting-edge projects like RAG-based chatbots, LLM-driven BI systems, and autonomous coding agents. You will collaborate cross-functionally with engineering teams to turn AI prototypes into scalable production systems.

Key Responsibilities :

Architect and implement end-to-end

Generative AI solutions

(e.g., RAG chatbots, AI-powered BI tools, code-generating agents)

Develop intelligent agents using

LangGraph

or similar orchestration frameworks

Build scalable data ingestion and retrieval pipelines leveraging

LlamaIndex

and related libraries

Design and maintain high-performance

vector databases

for semantic search and information retrieval

Integrate and benchmark

multiple LLM providers

(OpenAI, Gemini, Claude, etc.)

Set up monitoring and observability systems using tools like

LangSmith

for real-time tracking of AI performance

Work closely with engineering teams to

productionize

machine learning models and applications

Required Skills & Qualifications :

3–7 years total experience, with a minimum of 1 year focused on Generative AI

Generative AI Expertise :

Practical experience with

LangGraph

or equivalent frameworks for agent orchestration

Strong knowledge of

LlamaIndex ,

LangChain , or similar libraries for document processing

Proficiency with

vector databases

(Pinecone, Chroma, Weaviate, etc.)

Familiarity with LLM APIs from providers like

OpenAI ,

Anthropic , and

Google

Hands-on experience with

LLM observability tools

such as LangSmith, Weights & Biases

Demonstrated ability to build

natural language to SQL BI tools

Proven experience in building

RAG systems

for contextual chatbot solutions

Experience in developing

code generation agents

and LLM-based programming assistants

Traditional AI & Machine Learning :

Solid foundation in ML techniques such as

classification, regression, clustering, and time-series forecasting

Proficiency with frameworks like

scikit-learn ,

TensorFlow , and

PyTorch

Experience in

statistical analysis ,

A / B testing , and

experimental design

Strong data handling skills, including

feature engineering

and

preprocessing

Note :

If you are matching on to the above job description & skills, please fill in your details on the below Form enclosed (https : / / forms.gle / bUyXMBhgSxxBZVeK9)