Senior AI Systems Architect

4 semanas atrás


Lisboa, Lisboa, Portugal Robert Walters Plc Tempo inteiro

We are seeking a highly skilled Senior AI Systems Architect to lead the design and implementation of scalable, high-performance distributed systems and microservices. This individual will have a strong foundation in software engineering and a passion for building high-quality, data-intensive, and AI-powered systems. The successful candidate will have the autonomy to lead complex projects while collaborating with cross-functional teams to deliver impactful solutions.

Key Responsibilities:

  • Design and implement scalable, high-performance 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.
  • Make data-driven decisions to address system issues or enhance functionality.

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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