GenAI Developer

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Infosys Bengaluru seeks a GenAI developer to design and implement AI-powered solutions. You will leverage Python and LLMs to build chatbots, automation, and enterprise integrations, focusing on retrieval-augmented generation and prompt optimization.

Role requires hands-on work with LangChain, LlamaIndex, and vector databases; familiarity with REST APIs and cloud platforms; strong problem-solving and communication skills.

Qualifications

• Strong programming experience in Python.
• Hands-on experience with Generative AI, LLMs, and Prompt Engineering.
• Familiarity with RAG and vector databases.
• Experience building GenAI apps with LLMs and API integration.
• Knowledge of LangChain, LlamaIndex, and vector stores.

Responsibilities

• Design and develop GenAI applications using LLMs such as GPT or similar models.
• Build and optimize Retrieval-Augmented Generation (RAG) solutions.
• Develop AI-powered chatbots, virtual assistants, and automation.
• Create and manage prompts for model performance.
• Integrate AI with APIs, databases, and enterprise apps.
• Fine-tune and evaluate LLMs for business use cases.
• Collaborate with cross-functional teams to deliver scalable AI solutions.

Skills

Python programming

Generative AI

LLMs

Prompt engineering

RAG

LangChain

LlamaIndex

Vector databases

REST APIs

Cloud platforms

ML concepts

NLP concepts

Problem solving

Communication skills

Tools

LangChain

LlamaIndex

FAISS

Pinecone

ChromaDB

Job description

Strong programming experience in Python. Hands-on experience with Generative AI, LLMs, Prompt Engineering, and RAG. Knowledge of LangChain, LlamaIndex, Vector Databases (FAISS, Pinecone, ChromaDB). Experience with REST APIs and cloud platforms (Azure/AWS/GCP). Understanding of Machine Learning and NLP concepts. Good problem-solving and communication skills.

Design and develop GenAI applications using LLMs such as GPT, Llama, Gemini, or similar models. Build and optimize RAG (Retrieval-Augmented Generation) based solutions. Develop AI-powered chatbots, virtual assistants, and intelligent automation solutions. Create and manage prompts for improved model performance and accuracy. Integrate AI solutions with APIs, databases, and enterprise applications. Fine-tune and evaluate LLMs for specific business use cases. Collaborate with cross-functional teams to deliver scalable AI solutions.

Experience with model fine-tuning and AI agent frameworks. Knowledge of MLOps and AI deployment practices. Familiarity with Azure OpenAI Services.