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, 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.