Python Engineer

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