Building Scalable Production Systems

Há 3 dias

Brasil beBeeSystem Tempo inteiro US$120.000 - US$200.000
System Architect Specialist

We are seeking a skilled System Architect Specialist to join our team of experts. As a seasoned professional, you will play a crucial role in the development and maintenance of large-scale production systems.

This is an excellent opportunity for those who enjoy working on complex systems and have experience with performance, scalability, and reliability.

Key Responsibilities:
  • System Architecture: Design, develop, and maintain high-reliability systems and pipelines that scale to millions of requests per second on large volumes of data.
  • System Optimization: Ensure aspects such as observability, automation, reliability, scalability, continuous integration, and security across multiple business domains in a platform-oriented way.
  • Collaboration: Collaborate with other developers from multiple teams to integrate their work within our infrastructure.
  • Code Reviews: Participate in code reviews and take part in architecture and design sessions.
  • Technology Updates: Stay up-to-date with recent developments in relevant technologies and assess their applicability.
  • Workflow Development: Contribute to maintaining, extending, and improving existing workflows and implement new ones to handle high-volume data flows.
Requirements:
  • Professional Experience: 4+ years of experience building and maintaining large-scale production systems with a focus on performance, scalability, and reliability.
  • Coding Skills: Significant experience coding and developing in Python.
  • Infrastructure Management: Passion for improving existing infrastructure and expertise in orchestration platforms: Kubernetes, containerization, and microservice design; event-driven model for workflow orchestration, monorepo-scale CI/CD, and testing.
  • Database Systems: Experience with database systems (SQL, NoSQL), distributed systems, and architectures.
  • Machine Learning Fundamentals: Familiarity with machine learning fundamentals such as data preparation, model training, model evaluation, and model inference.
  • Code Quality: Focus on clearly structured, maintainable, well-documented, and tested code, including unit, integration, and end-to-end tests.

At our company, we celebrate diversity and are committed to creating an inclusive environment for all members of our team. We welcome applications from candidates who share our values and passion for technology.

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