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