Junior Python Developer

Role Overview

We are seeking a motivated Junior Python Developer with 1 to 1.5 years of experience to join our team in Indore for a Full-Time, On-Site position. The role involves developing and maintaining backend applications, focusing heavily on modern Python frameworks and integrating Generative AI technologies.

Responsibilities

• Develop, maintain, and optimize backend applications using Python.
• Design and develop RESTful APIs using FastAPI, Flask, and Django.
• Build scalable, secure, and high-performance backend services.
• Integrate third-party APIs and internal microservices.
• Develop and support AI-powered applications using Large Language Models (LLMs).
• Assist in building Retrieval-Augmented Generation (RAG) pipelines and GenAI solutions.
• Deploy, monitor, and maintain applications on AWS cloud services such as EC2, S3, Lambda, API Gateway, IAM, CloudWatch, and RDS.
• Write clean, reusable, well-documented, and testable code.
• Debug, troubleshoot, and optimize application performance.
• Collaborate with cross-functional teams.
• Participate in code reviews and follow coding standards and best practices.

Requirements

• Strong programming skills in Python.
• Hands-on experience with FastAPI, Flask, and Django.
• Experience in developing and consuming RESTful APIs.
• Good understanding of Object-Oriented Programming (OOP).
• Knowledge of SQL databases such as PostgreSQL or MySQL.
• Basic knowledge of Generative AI, including LLMs, Prompt Engineering, RAG, Embeddings, and Vector Databases.
• Familiarity with AI frameworks such as LangChain or LangGraph.
• Basic knowledge of AWS services such as EC2, S3, Lambda, API Gateway, IAM, CloudWatch, and RDS.
• Experience with Git, GitHub, Docker, Postman, and unit testing frameworks.
• Good understanding of software development best practices and Agile methodologies.
• Strong problem-solving, English communication, and teamwork skills.

Nice to Have:

• Knowledge of AI Agent workflows and multi-agent architectures.
• Experience with Model Context Protocol (MCP) and MCP tools.
• Basic understanding of Machine Learning concepts and model lifecycle.
• Knowledge of Docker, Kubernetes, and CI/CD pipelines.