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.

OK

OK