Senior Distributed Systems Architect
3 semanas atrás
Roland's Role: As a Principal AI Engineer at Robert Walters Plc, you will be part of a dynamic team that is passionate about building high-quality AI-powered systems. Your expertise in designing, implementing, and optimizing scalable distributed systems and microservices will be invaluable to our organization.
About the Opportunity: This is an exciting chance to lead complex projects and collaborate with cross-functional teams to deliver impactful solutions. Your deep understanding of distributed systems, microservices architecture, and extensive experience in Python will enable you to make data-driven decisions and drive system enhancements.
Responsibilities:
- Design, implement, and optimize scalable distributed systems and microservices
- Develop and maintain systems using Python and other relevant technologies
- Utilize message brokers such as Kafka or RabbitMQ to design and implement messaging patterns
- Work autonomously on highly complex tasks, ensuring performance, security, observability, and code quality
- Lead and participate in the implementation of DevOps/MLOps practices, including containerization technologies (Docker, Kubernetes, etc.)
- Collaborate with cross-functional teams, providing technical insights and guidance to stakeholders
- Monitor, troubleshoot, and improve production systems to ensure optimal performance and uptime
Requirements:
- 5+ years of experience with Python in production environments
- 10+ years of experience in software development, working with a diverse set of programming languages and paradigms
- Proven track record of designing, implementing, and scaling performant distributed systems and microservice architectures
- Deep understanding of classic Machine Learning, Deep Learning, and Generative AI algorithms
- Familiarity with the ML development lifecycle and its differences from traditional software development workflows
- Experience with message brokers such as Kafka or RabbitMQ and understanding of messaging patterns
- Solid experience in DevOps/MLOps practices, including containerization technologies (e.g., Docker, Kubernetes)
- Familiarity with big data technologies such as Apache Spark, Delta Lake, Apache Kafka, Apache Flink, and NoSQL databases
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