Senior Staff, Software Engineering

Warner Bros Discovery Warner Bros Discovery · Media · Hyderabad, Telangāna, India · Technology

Senior Staff Software Engineer responsible for designing and delivering software platforms and services that process billions of ad events daily. This role involves setting technical standards, modernizing legacy components into cloud-native services, and ensuring reliable, secure, and cost-efficient delivery of mission-critical capabilities for monetization and decisioning. Key responsibilities include owning large-scale event-driven systems, architecting low-latency services, designing data pipelines, optimizing systems, defining SLOs/SLAs, leading platform modernization, embedding observability, driving cost efficiency, partnering with Data Science to productionize ML models into low-latency services, designing APIs, ensuring privacy-safe data usage, and providing technical leadership and mentorship.

What you'd actually do

  1. Own the design and evolution of large-scale, event-driven systems powering real-time and batch processing across multi-billion event pipelines.
  2. Architect low-latency, high-throughput services for ad decisioning, targeting, and measurement
  3. Lead the transformation of legacy AdTech systems into modular, extensible, cloud-native platforms.
  4. Partner with Data Science to productionize ML models (forecasting, optimization, personalization) into low-latency services
  5. Act as a technical anchor across teams, raising the bar for design, reliability, and engineering rigor.

Skills

Required

  • AWS/GCP/Azure
  • Docker
  • Kubernetes
  • Kafka
  • Kinesis
  • Pub/Sub
  • CI/CD
  • automated testing
  • observability
  • incident management
  • SLOs
  • on-call
  • distributed systems
  • backend systems
  • API design
  • high availability
  • performance requirements

Nice to have

  • PhD in distributed systems or statistical optimization
  • AdTech Domain Knowledge
  • mentoring junior engineers

What the JD emphasized

  • productionize ML models
  • low-latency services
  • large-scale, event-driven systems
  • multi-billion event pipelines
  • cloud-native platforms

Other signals

  • productionize ML models
  • low-latency services
  • large-scale, event-driven systems
  • multi-billion event pipelines
  • cloud-native platforms