Job Description
We are seeking a highly skilled Lead 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
- 6+ years 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.
Additional Information
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.
Education
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
