Python Engineer

Key Responsibilities

• Design, develop, test, and maintain robust Python applications and services.

• Develop RESTful APIs and microservices using frameworks such as FastAPI, Flask, or Django.

• Write clean, reusable, and efficient code following best practices and coding standards.

• Collaborate with cross-functional teams to design and implement scalable software solutions.

• Optimize application performance, reliability, and security.

• Integrate applications with third-party APIs, databases, and cloud services.

• Troubleshoot, debug, and resolve production issues efficiently.

• Develop automated unit, integration, and performance tests.

• Participate in code reviews and mentor junior developers.

• Work in Agile/Scrum teams to deliver high-quality software within project timelines.

• Create and maintain technical documentation for applications and APIs.

• Support document processing, workflow automation, and data indexing solutions where applicable.

Required Skills

Programming

• Python (Advanced) 
• Object-Oriented Programming (OOP) 
• Data Structures & Algorithms 
• Multithreading and Asynchronous Programming 

Web Frameworks

• FastAPI (preferred)
• Flask 
• Django

API Development

• REST APIs 
• JSON 
• OpenAPI/Swagger 
• API Security (OAuth2, JWT) 

Databases

• PostgreSQL 
• MySQL 
• MongoDB 
• Redis 

Cloud & DevOps

• AWS, Azure, or Google Cloud Platform 
• Docker 
• Kubernetes (preferred) 
• CI/CD pipelines 
• Git/GitHub/GitLab/Azure DevOps 

Messaging & Caching

• RabbitMQ 
• Apache Kafka (preferred) 
• Redis Cache 
• Celery

Testing

• PyTest 
• Unit Testing 
• Integration Testing 
• Mocking Frameworks 

Development Tools

• Visual Studio Code (VS Code) 
• PyCharm 

Required Experience

• 5–10 years of hands-on experience in Python application development.

• Strong experience developing RESTful APIs using FastAPI, Flask, or Django.

• Experience with relational and NoSQL databases.

• Knowledge of microservices architecture and distributed systems.

• Experience with cloud platforms such as AWS, Azure, or GCP.

• Familiarity with containerization using Docker and orchestration with Kubernetes.

• Experience implementing CI/CD pipelines and version control using Git.

• Strong debugging, troubleshooting, and performance optimization skills.

• Experience working in Agile/Scrum environments.

Good to Have

• Basic understanding of Generative AI concepts and LLM usage.

• Experience with prompt engineering for classification, extraction, or summarization tasks.

• Familiarity with embeddings, semantic search, or retrieval-augmented generation (RAG).

• Exposure to OCR tools, PDF/document parsing, or workflow automation.

• Experience building AI-assisted features or human-in-the-loop review workflows.