CoE - Digital Engineering - Backend Developer

Quality Ai; Hinoba-an; On-site; PHP 594,000 - 858,000; Full time

Job summary

QualityAI is seeking a highly motivated Python Developer with 3–5 years of hands-on experience to design, develop, and deploy scalable backend applications. You’ll work with Python frameworks, REST APIs, and cloud-native tech, including Docker and Kubernetes.

Exposure to AI/LLM tech is a plus. You’ll collaborate with DevOps on CI/CD pipelines and deliver reliable, scalable services across cloud platforms.

Qualifications

• 3–5 years of professional Python development.
• Experience with FastAPI/Flask/Django frameworks.
• Developing REST APIs and microservices.
• Solid OOP and design patterns knowledge.
• Hands-on with Docker containers and Kubernetes deployments.
• Cloud platforms: Azure, AWS, or Google Cloud.
• Database experience: PostgreSQL/MySQL and MongoDB.
• Git and version control workflows; Linux shell.
• Familiarity with CI/CD tools and practices.

Responsibilities

• Design, develop, test, and maintain scalable Python apps and microservices.
• Build and consume RESTful APIs; integrate with external services.
• Develop cloud-native applications using modern practices.
• Containerize with Docker; deploy on Kubernetes.
• Work with cloud platforms like Azure/AWS/GCP.
• Optimize performance, scalability, and reliability.
• Collaborate with DevOps to implement CI/CD pipelines.
• Troubleshoot production issues; ensure high availability.
• Participate in code reviews and follow best practices.
• Write clean, well-documented code.

Skills

Python

FastAPI/Flask/Django

REST APIs

OO Design Patterns

Docker

Kubernetes

Cloud Platforms

PostgreSQL/MySQL

MongoDB

Git

Linux

CI/CD

Tools

Docker

Kubernetes

GitHub Actions

Jenkins

Azure DevOps

GitLab CI

Job description

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Date: 2 Sept 2026

Company: QualityAI

Country/Region: IN

About the Role We are looking for a highly motivated Python Developer with 3–5 years of hands-on experience in designing, developing, and deploying scalable backend applications. The ideal candidate should have strong expertise in Python, cloud-native development, containerization, and Kubernetes. Exposure to AI/LLM technologies will be a significant advantage.

Key Responsibilities

• Design, develop, test, and maintain scalable Python applications and microservices.
• Develop and consume RESTful APIs and integrate with third-party services.
• Build cloud-native applications using modern development practices.
• Containerize applications using Docker and deploy them on Kubernetes.
• Work with cloud platforms such as Azure, AWS, or Google Cloud Platform.
• Optimize application performance, scalability, and reliability.
• Collaborate with DevOps teams to implement CI/CD pipelines and automated deployments.
• Troubleshoot production issues and ensure high system availability.
• Participate in code reviews and follow software engineering best practices.
• Write clean, maintainable, and well-documented code.

Required Skills

• 3–5 years of professional experience in Python development.
• Strong understanding of Python frameworks such as FastAPI, Flask, or Django.
• Experience in developing REST APIs and microservices.
• Good knowledge of object-oriented programming and design patterns.
• Hands-on experience with Docker and containerized application development.
• Experience deploying and managing applications on Kubernetes.
• Knowledge of cloud platforms (Azure, AWS, or Google Cloud Platform).
• Experience with relational databases (PostgreSQL/MySQL) and NoSQL databases (MongoDB).
• Familiarity with Git and version control workflows.
• Experience with Linux environments and shell scripting.
• Understanding of CI/CD tools such as GitHub Actions, Jenkins, Azure DevOps, or GitLab CI.
• Strong debugging, analytical, and problem-solving skills.

Preferred Skills

• Experience with AI/ML applications or Generative AI.
• Familiarity with Large Language Models (LLMs) such as OpenAI GPT, Claude, Gemini, or Llama.
• Experience using AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or CrewAI.
• Knowledge of vector databases such as Pinecone, Weaviate, Milvus, or ChromaDB.
• Experience with Retrieval-Augmented Generation (RAG), prompt engineering, and AI agent development.
• Exposure to message brokers such as RabbitMQ, Kafka, or Azure Service Bus.