Python Backend Developer

About the role:

The IT Contract Management Specialist is responsible for the effective management of the company’s IT contracts, ensuring accuracy, compliance, and adherence to internal policies and external regulations. They will review and administer IT contracts in collaboration with various departments and external partners, securing optimal IT solutions contributing to the company’s strategic objectives.

Responsibilities:

• Design, develop, and maintain scalable backend systems using Python
• Build and optimize RESTful APIs and real-time communication services
• Collaborate with cross-functional teams to deliver high-quality software solutions
• Ensure code quality through testing, code reviews, and CI/CD practices
• Integrate AI services and data platforms to enhance application intelligence
• Develop and deploy machine learning workflows and generative AI capabilities
• Implement Retrieval-Augmented Generation (RAG) and agentic AI systems

What we are looking for:

• Advanced Python: Writing clean, efficient, and maintainable code
• Object-Oriented Programming (OOP): Strong grasp of design principles and patterns
• Asynchronous Programming: Experience with asyncio, aiohttp for non-blocking operations
• FastAPI and ORMs: Building APIs and web apps using FastAPI and SQLAlchemy
• PostgreSQL: Schema design, query optimization, and performance tuning
• HTTP and WebSockets: RESTful API development and real-time communication
• Docker and Kubernetes: Containerization and orchestration for scalable deployments
• CI/CD Pipelines: Automated testing and deployment using CI/CD tools such as Jenkins
• Testing Frameworks: Unit and integration testing with pytest
• Version Control: Git and Bitbucket for source code management and collaboration
• User Authentication: OAuth2, implicit flow, code flow
• Azure Entra ID: Integration for identity and access management
• Security Best Practices: Secure coding, data encryption, and vulnerability mitigation
• Large Language Models (LLMs): Integration of generative AI capabilities into applications
• Databricks: ETL pipelines, analytics, machine learning workflows, vector search
• Retrieval-Augmented Generation (RAG): Enhancing AI with contextual data retrieval
• Agentic AI: Designing autonomous agents for complex tasks
• Frontend Development (React): Basic proficiency in building interactive UIs and integrating with backend services