Senior Python Developer

Job Description

We are seeking a highly skilled Senior Python Engineer with extensive experience in FastAPI and microservices architecture to join our dynamic team. The ideal candidate will have a strong technical background, proven leadership in technical teams, and expertise in building scalable, resilient, and secure applications.

Key Responsibilities:

• Lead the design, development, and deployment of applications using microservice architecture.

• Develop and maintain FastAPI-based backend services with high performance and scalability.

• Implement best practices in logging, monitoring, health checks, scalability, resilience, service discovery, API gateways, and error handling. • Ensure code quality, security, and performance optimization.

• Work with containerization technologies like Docker and Kubernetes for application deployment.

• Collaborate with cross-functional teams to define, design, and ship new features.

• Establish and manage CI/CD pipelines for seamless application deployment.

• Implement best practices for API design, development, and security.

• Set up and maintain monitoring and logging tools (e.g., Prometheus, Grafana).

• Ensure adherence to version control systems (e.g., Git) and collaborative workflows.

Qualifications

• Proven experience in leading technical teams and developing applications using microservice architecture.

• Strong proficiency in Python and FastAPI.

• Deep understanding of Pydantic for data validation in FastAPI.

• Experience with containerization (Docker, Kubernetes).

• Familiarity with CI/CD pipelines and automation tools.

• Knowledge of API design and implementation best practices.

• Experience working with monitoring and logging tools (e.g., Prometheus, Grafana).

• Strong understanding of security best practices in microservices-based applications.

Nice to Have:

• Experience with Retriever models, including implementation of chunking strategies.

• Familiarity with vector databases and their use cases.

• Understanding of optimal approaches in querying LLM models via API.

• Experience with prompt engineering and different strategies for effective interactions with LLMs.

• Exposure to various prompt engineering techniques in different scenarios