Python Developer

Required Qualifications:

• Experience: 8+ years of professional software development experience, primarily focused on backend systems using Python.
• Core Backend: Expert proficiency in Python and developing high-performance RESTful APIs, with specific, demonstrable experience using FastAPI.
• API Standards: Deep understanding and practical experience defining APIs using the OpenAPI Specification (OAS), including tooling for validation and documentation.
• Architecture: Proven history of designing, deploying, and maintaining systems built on Microservice Architectures.
• Data Layer: Expertise with relational databases and using advanced Database ORM features for complex query optimization and schema migrations.
• Workflow Systems: Experience defining, implementing, and managing complex business logic using step-based, state-driven, or declarative workflow systems (e.g., orchestration tools, custom state machines).
• Cloud & Data: Strong experience working with cloud environments (AWS, GCP, or Azure) and significant experience integrating systems with Snowflake.
• Preferred Qualifications (Nice-to-Haves)
• Experience in integrating AI-Driven Development principles into software lifecycles.
• Experience with AI Editors (Cursor, Windsurf etc) for coding
• Understanding on RAG and AI applications
• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.
• Knowledge of asynchronous programming patterns and performance tuning in Python (asyncio).

Key Responsibilities:

Architectural Design & Implementation:

• Microservices: Lead the design and implementation of robust, scalable, and secure microservices using Python and FastAPI (or similar asynchronous frameworks).
• API Specification/AI Native Development: Define, document, and maintain all service endpoints using the OpenAPI Specification (OAS) standard to ensure consistency, clarity, and ease of consumption by frontend and internal teams.
• Workflow Systems: Design and implement resilient, step-based state machines or declarative Workflow Systems to manage complex, multi-step business logic and data processing pipelines.

AI Enablement & Data Integration:

• AI-Driven Development: Integrate machine learning models (AI/ML) into production microservices.
• Data Integration: Architect and develop robust data synchronization with experience in Snowflake integrations (e.g., using Snowflake Python Connector or ORM extensions) to handle large-scale analytical and transactional data flows.
• Data Persistence: Implement and optimize data models and persistence layers using modern Database ORMs (e.g., SQLAlchemy, SQLModel) for relational and NoSQL databases.

Engineering Quality & Best Practices :

• Code Quality: Define and enforce organization-wide Code Base Best Practices and rigorous Code Quality standards, including performance, security, and maintainability.
• Testing: Establish comprehensive Unit Test Cases, integration tests, and end-to-end testing strategies to ensure high coverage and reliability across all services.
• Mentorship: Provide technical leadership, mentorship, and code reviews to mid and senior-level engineers, fostering a culture of technical excellence.