Senior Generative AI Engineer (LLM, RAG & Machine Learning)_XP:8 +

Tata Consultancy Services; Hyderabad, Pune District, Bengaluru; On-site; INR 3,800,000 - 6,500,000; Full time

Job summary

Tata Consultancy Services seeks a Senior Generative AI Engineer (LLM, RAG & Machine Learning) to design and deploy enterprise-grade GenAI solutions. You will work with LLMs, RAG architectures, and Python-based AI services to deliver scalable applications.

You will build AI solutions leveraging vector databases, LangChain, and prompt engineering, while developing ML models including time series forecasting and predictive analytics.

Qualifications

• Experience designing and deploying enterprise-grade Generative AI systems.
• Strong proficiency with LLMs, RAG architectures, and API-based integrations.
• Hands-on Python development for AI/ML applications and services.

Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI solutions using LLMs and RAG architectures.
• Build and optimize AI applications leveraging Vector Databases, LangChain, and Prompt Engineering techniques.
• Develop Machine Learning models, including Time Series Forecasting and predictive analytics solutions.
• Implement scalable Python-based AI/ML applications and APIs.
• Evaluate, fine-tune, and deploy AI models for production environments.
• Collaborate with stakeholders to translate business requirements into AI-driven solutions.
• Ensure performance, scalability, security, and reliability of GenAI applications.
• Contribute to solution design, effort estimation, and technical documentation.
• Stay current with emerging AI technologies, frameworks, and industry best practices.

Skills

Generative AI

LLM

RAG

Python

Machine Learning

NLP

Vector Databases

LangChain

Prompt Engineering

Agentic AI

OpenAI / Azure OpenAI

Time Series Forecasting

Model Deployment

Job description

Senior Generative AI Engineer (LLM, RAG & Machine Learning) | 6-12 Years

Key Skills

• Generative AI
• Large Language Models (LLM)
• Retrieval Augmented Generation (RAG)
• Python Programming
• Machine Learning
• Natural Language Processing (NLP)
• Vector Databases
• LangChain
• Prompt Engineering
• Agentic AI
• OpenAI / Azure OpenAI
• Time Series Forecasting
• Model Deployment

Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI solutions using LLMs and RAG architectures.
• Build and optimize AI applications leveraging Vector Databases, LangChain, and Prompt Engineering techniques.
• Develop Machine Learning models, including Time Series Forecasting and predictive analytics solutions.
• Implement scalable Python-based AI/ML applications and APIs.
• Evaluate, fine-tune, and deploy AI models for production environments.
• Collaborate with stakeholders to translate business requirements into AI-driven solutions.
• Ensure performance, scalability, security, and reliability of GenAI applications.
• Contribute to solution design, effort estimation, and technical documentation.
• Stay current with emerging AI technologies, frameworks, and industry best practices.