Python Engineer

Job description

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.