Generative AI, Rag, Python

Infosys; Bengaluru, Mumbai; Hybrid; INR 1,400,000 - 2,400,000; Full time

Job summary

Infosys is seeking a highly skilled Generative AI Engineer to design, develop, and deploy enterprise-grade GenAI solutions. The role focuses on Python development, RAG pipelines, LLM integration, and building intelligent assistants and document processing tools.

You will work with vector databases, embeddings, and cloud AI services to solve complex business problems, collaborating with data scientists, architects, and engineering teams.

Qualifications

• Experience in Generative AI and enterprise GenAI solutions.
• Strong Python development experience.
• Hands-on work with RAG pipelines, embeddings, and vector stores.

Responsibilities

• Design Generative AI applications using Python and modern AI frameworks.
• Build RAG pipelines for enterprise search and knowledge management.
• Integrate LLMs with enterprise apps and workflows.
• Develop chatbots, copilots, and document processing solutions.
• Apply prompt engineering, evaluation, and optimization techniques.
• Work with vector databases, embeddings, and semantic search.

Skills

Python

RAG

LLMs

AI development

Vector databases

Cloud services

APIs & microservices

Prompt engineering

Job description

Job Title

Generative AI Engineer RAG & Python

Experience

5 to 8 Years

Job Summary

We are looking for a highly skilled Generative AI Engineer with expertise in Python, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and AI application development. The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade GenAI solutions leveraging LLMs, vector databases, and cloud AI services to solve complex business problems.

Key Responsibilities

• Design and develop Generative AI applications using Python and modern AI frameworks.
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines for enterprise search and knowledge management solutions.
• Integrate Large Language Models (LLMs) with enterprise applications and business workflows.
• Develop intelligent chatbots, copilots, virtual assistants, and document processing solutions.
• Implement prompt engineering, model evaluation, and response optimization techniques.
• Work with vector databases, embeddings, and semantic search technologies.
• Develop scalable APIs and microservices for AI-powered applications.
• Deploy AI solutions on cloud platforms and ensure performance, monitoring, and security.
• Collaborate with Data Scientists, Product Owners, Architects, and Engineering teams.
• Follow Responsible AI and g …