Full Stack

Role Overview

We are looking for an experienced Full Stack Python Developer with strong expertise in backend development using Python and FastAPI, frontend development using React, and containerized application deployment using Docker and Kubernetes.

The ideal candidate should have hands-on experience building scalable, high-performance applications, developing RESTful APIs, working with databases and messaging systems, and implementing CI/CD pipelines.

Additionally, the candidate should have practical experience using Large Language Models (LLMs), particularly in prompt engineering and integrating AI-powered capabilities into applications. Exposure to frameworks such as LangChain, LangGraph, LangSmith, and Model Context Protocol (MCP) would be an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python and FastAPI.
  
• Build responsive and user-friendly frontend applications using React.
  
• Develop and integrate RESTful APIs and ensure seamless communication between frontend and backend systems.
  
• Design, optimize, and manage PostgreSQL databases, including writing complex SQL queries, joins, stored procedures, and performance optimization.
  
• Implement asynchronous processing and messaging mechanisms using RabbitMQ (RMQ).
  
• Utilize Redis for caching, session management, and performance optimization.
  
• Containerize applications using Docker and manage deployments using Kubernetes.
  
• Develop, maintain, and optimize CI/CD pipelines, preferably using GitHub Actions.
  
• Implement LLM-based application features using effective prompt engineering techniques.
  
• Integrate LLM capabilities into existing applications and workflows.
  
• Collaborate with cross-functional teams to design, develop, test, and deploy scalable software solutions.
  
• Ensure application performance, security, reliability, and maintainability.
  

Mandatory Technical Skills

1. Backend Development: Strong proficiency in Python and FastAPI.
   
2. Frontend Development: Hands-on experience with React.
   
3. Containerization & Orchestration: Practical experience with Docker and Kubernetes.
   
4. Database Management: Strong PostgreSQL knowledge, particularly writing complex SQL queries and query optimization.
   
5. Message Queuing: Experience with RabbitMQ (RMQ).
   
6. Caching: Hands-on experience with Redis.
   
7. CI/CD: Experience building and maintaining CI/CD pipelines, preferably using GitHub Actions.
   
8. AI/LLM: Practical experience with LLM prompt engineering and integrating LLM-powered capabilities into applications.
   

Good-to-Have Skills

• Experience with LangChain for LLM application development.
  
• Knowledge of LangGraph for building stateful and multi-agent AI workflows.
  
• Familiarity with LangSmith for LLM application testing, tracing, and monitoring.
  
• Understanding of Model Context Protocol (MCP) and its implementation for connecting AI applications with external tools and data sources.
  
• Exposure to RAG (Retrieval-Augmented Generation), AI agents, and LLM-based application architectures.
  

Desired Candidate Profile

• Strong problem-solving and analytical skills.
  
• Ability to design and develop scalable, distributed applications.
  
• Good understanding of software engineering principles and application architecture.
  
• Ability to work independently as well as collaboratively within an agile development environment.
  
• Strong debugging, troubleshooting, and performance optimization capabilities.