Distributed Systems Engineer 5 - Ads Creative Infrastructure

Netflix Netflix · Big Tech · New York, NY +3 · Engineering

Netflix is seeking a Distributed Systems Engineer to build and maintain the scalable backbone for their Ads Platform's creative workflows. This role involves designing and implementing highly available, fault-tolerant distributed systems to process, review, and deploy ad creatives efficiently. The engineer will focus on infrastructure that supports various supply sources, leverages ML/genAI algorithms, and manages distribution for ad decisioning and serving across a wide range of devices. The position requires deep expertise in distributed systems, programming in Java, Python, or Go, and strong operational skills with monitoring and observability tools.

What you'd actually do

  1. Build out our creative infrastructure that works across our broadening supply sources (SVOD, Live and FTAB), enables scalability and sophistication (leveraging the best in class ML / genAI algorithms) and manages effective distribution for ad decisioning and serving even as we bring in more cardinality and flexibility of units that span a large variety of devices.
  2. Design, build, and maintain highly available, fault-tolerant, and scalable distributed systems. This includes a strong understanding of concurrency, parallel processing, and microservices architecture.
  3. Set up and maintain comprehensive monitoring, logging, tracing, and alerting systems (e.g., using tools like Spinnaker, Prometheus, Grafana, or proprietary solutions) to ensure system reliability and quick diagnosis of issues.
  4. Tackle complex, ambiguous technical problems and develop pragmatic, long-term solutions.
  5. Collaborate with cross-functional teams (e.g., Product Management, Design, and other Engineering teams).

Skills

Required

  • Distributed Systems
  • Java
  • Python
  • Go
  • Observability
  • Monitoring
  • Logging
  • Tracing
  • Alerting
  • Problem-Solving
  • Collaboration
  • Communication

Nice to have

  • Ads Domain
  • creative management
  • ad serving
  • campaign optimization platforms
  • creative lifecycle management
  • pipeline development
  • machine learning applications in advertising
  • ad review systems
  • real-time, low-latency online advertising environments
  • CTV space

What the JD emphasized

  • leveraging the best in class ML / genAI algorithms
  • creative infrastructure
  • distributed systems