Gen AI Agent Developer

Tata Consultancy Services; Hyderabad, Pune District, Chennai District; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Tata Consultancy Services is seeking a Gen AI Agent Developer with strong NLP and ML background in Hyderabad. The role emphasizes building GenAI applications, LLM-based pipelines, and retrieval systems using vector databases.

Expect hands-on work with LangChain, LlamaIndex, and cloud deployment across AWS/Azure/GCP. Strong Python expertise and data science tooling are essential for delivering impactful AI solutions.

Qualifications

• 5-10 years of professional experience in data science, ML and AI with NLP/LLMs and GenAI.
• Bachelor's or Master's in CS, Statistics, Mathematics, Engineering or related field.
• Strong Python and data science libraries (NumPy, Pandas, Scikit-learn) required.
• Proficient in PyTorch or TensorFlow; familiar with Hugging Face, NLTK, SpaCy.
• Experience building retrieval systems with vector databases and LangChain/LlamaIndex is preferred.

Skills

Python

NLP

LLMs

GenAI

NumPy

Pandas

Scikit-learn

PyTorch

TensorFlow

HuggingFace

NLTK

SpaCy

LangChain

LlamaIndex

Vector Databases

SQL

AWS

Azure

GCP

Education

Bachelor's or Master's degree in a quantitative field

Tools

LangChain

LlamaIndex

Vector DB

Cloud Platforms

Job description

Role: Gen AI Agent Developer

Experience: 6 - 10 Years

Skills: Langchain, Vector database

JD

Experience: 5-10 years of professional experience in data science, machine learning, and AI, with specific experience in NLP, LLMs, and GenAI applications.

• Education: Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, or a related discipline.


• Programming Languages: Strong proficiency in Python is mandatory, with experience in data science libraries like NumPy, Pandas, and Scikit-learn. Knowledge of SQL is also essential for data extraction and manipulation.


• AI/ML Frameworks: Expertise in deep learning frameworks such as PyTorch and TensorFlow. Familiarity with Hugging Face transformers, NLTK, or SpaCy is also common.


• GenAI/NLP Specific Tools & Techniques: Experience with LLM frameworks like LangChain and LlamaIndex. Knowledge of building retrieval systems using vector databases (e.g., Pinecone, Weaviate, ChromaDB, FAISS). Proficiency in NLP techniques including embeddings, topic modeling, text classification, semantic search, and summarization.


• Cloud Platforms: Hands-on experience with major cloud computing services (AWS, Azure, GCP) for model deployment and leveraging services like Azure OpenAI, Google Vertex AI, or AWS Bedrock.


• Problem-Solving: Strong analytical, problem-solving, and statistical skills.