Server Infrastructure Engineer

San Francisco, CA, United States Posted 6 days ago

The infrastructure underpinning our efforts to map the world and make it editable is highly data-intensive. As an infrastructure engineer you are responsible for designing and building infrastructure components that are reliable at scale. You're not afraid of wrangling a malfunctioning system under pressure but you also understand the cost of pager pain from personal experience and work tirelessly to reduce operations costs instinctively. You're a team player because you know that the big problems worth solving can't be solved alone.

Ubiquity6 infrastructure is a devops-oriented team that invests continuously in automation and observability. We understand that high-performing teams are happy teams. Our systems are typically real-time or streaming-oriented, we value rigorous software engineering, high quality, fast execution, and teamwork.

To thrive on the team you should:

  • Have good intuition for the tradeoffs that need to happen every day to balance execution speed and code quality.
  • Be supportive and generous. You understand that a high functioning team means helping everyone around you level up.
  • Be comfortable taking risks. You know that hard problems don't always have easy or simple solutions.

The sort of technical skills we're looking for include:

  • Distributed systems experience. Retries and backoffs, circuit breakers, consistency models, consensus protocols, and replicated state machines have played a role in systems you've built at one time or another.
  • Experience building backend systems with AWS, GCP, Azure, or etc.
  • Experience building streaming processing systems and data pipelines and working with scalable pub-sub systems like Kafka, Kinesis, or Pulsar.
  • Have successfully built reasonably sophisticated infrastructure software components on a modern backend platform like Java, Scala, NodeJS, or Go.
  • Experience building large-scale analytic query infrastructure, caching systems, or distributed databases.
  • Experience scaling machine learning or computer vision infrastructure.
  • Experience operating high-performance infrastructure at scale, including experience debugging production systems.
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