Python Developer - AI & Large Language Models Engineer

Infosys; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Infosys in Bengaluru invites a Python Developer specializing in Agentic AI, LLMs, and RAG architectures to design and implement AI-driven solutions. You will work with LangChain, LangGraph, CrewAI and AutoGen to build scalable AI applications, APIs, and ML pipelines.

Strong emphasis on embeddings, vector databases, and cloud AI services; candidate should proficiently apply prompt engineering, model evaluation, and best-practice software development.

Qualifications

• Strong programming experience in Python.
• Hands-on with LLMs, Generative AI and RAG architectures.
• Experience with LangChain, LangGraph, CrewAI, AutoGen or equivalents.
• Knowledge of vector databases and embeddings.
• Experience with REST APIs and web frameworks (FastAPI/Flask/Django).
• Understanding of model evaluation, Git/CI/CD, and software best practices.
• Knowledge of cloud AI services (Azure OpenAI preferred).

Responsibilities

• Develop and maintain AI applications using Python.
• Design Agentic AI systems using LangChain, LangGraph, CrewAI, AutoGen.
• Build and optimize RAG pipelines with vector databases.
• Integrate and fine-tune LLMs including OpenAI, Azure OpenAI, and others.
• Develop APIs and microservices for AI applications.
• Implement prompt engineering and AI workflow orchestration.
• Collaborate with teams to translate requirements into AI solutions.
• Monitor and improve AI model performance and reliability.

Skills

Python

LLMs

Generative AI

Agentic AI

RAG architectures

Vector Databases

APIs & Web Frameworks

CI/CD & Git

Cloud AI services

Prompt engineering

Tools

LangChain

LangGraph

CrewAI

AutoGen

LlamaIndex

Pinecone

ChromaDB

Weaviate

FAISS

Azure AI Search

FastAPI

Flask

Django

REST APIs

Git

CI/CD

Azure OpenAI

Job description

Python Developer - Agentic AI / LLM / RAG Engineer

Required Skills

Strong programming experience in Python. Hands-on experience with LLMs, Generative AI, Agentic AI, and RAG architectures. Experience with LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, or equivalent frameworks. Knowledge of vector databases such as Pinecone, ChromaDB, Weaviate, FAISS, or Azure AI Search. Experience with REST APIs, FastAPI, Flask, or Django. Understanding of embeddings, semantic search, prompt engineering, and model evaluation. Experience with Git, CI/CD, and software development best practices. Knowledge of cloud AI services (Azure OpenAI preferred).

Preferred Skills

Experience with multi-agent architectures and AI orchestration. Knowledge of MLOps, model deployment, and containerization (Docker/Kubernetes). Exposure to NLP, machine learning, and deep learning concepts. Experience with enterprise AI governance, security, and responsible AI practices.

Technology Stack

Technology | Artificial Intelligence & Automation Skill Category | Python Development, Agentic AI, LLM, RAG, Generative AI Primary Skills | Python, LangChain, LangGraph, CrewAI, Azure OpenAI, RAG, Vector Databases Secondary Skills | FastAPI, Docker, Kubernetes, Azure AI Search, MLOps

Key Responsibilities

• Develop and maintain AI applications using Python.
• Design and implement Agentic AI systems using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
• Build and optimize RAG pipelines using vector databases and retrieval frameworks.
• Integrate and fine-tune Large Language Models (LLMs) including OpenAI, Azure OpenAI, Llama, Claude, Gemini, or similar.
• Develop APIs and microservices for AI applications.
• Implement prompt engineering, workflow orchestration, and AI agent collaboration patterns.
• Create scalable solutions using cloud platforms such as Azure, AWS, or GCP.
• Monitor, evaluate, and improve AI model performance, accuracy, and response quality.
• Collaborate with business and technology teams to translate requirements into AI-driven solutions.