• Design and operate globally distributed backend services • Make architectural decisions on internal service integrations • Manage the full lifecycle: planning, implementation, monitoring • Maintain infrastructure tooling and automation • Contribute to engineering standards and documentation • Evaluate and integrate AI tooling into engineering workflows

• Run the Infrastructure & Services layer for internal data organization • Design, build, maintain, and document internal platforms with focus on automation and reliability • Own stability, availability, and security of services • Engineer systems to be resilient by design • Support services that Product teams depend on • Work directly with Analysts, Scientists, and Engineers • Drive cost optimization and capacity planning • Diagnose hardware faults and dispatch remote hands • Champion automation and engineering best practices • Help shape the structure, tooling, and future direction of the team

• Design, build, and improve monitoring pipelines and observability tooling across globally distributed infrastructure • Define and implement service-level monitoring based on golden signals (latency, traffic, errors, saturation) • Reduce alert fatigue - build meaningful, actionable alerts that engineers trust • Develop and maintain custom exporters, scripts, and integrations for metrics and log collection • Collaborate with the data team on anomaly detection and data-driven operational insights • Understand service signals - know what to measure, why, and what the numbers actually mean

• Ensure content accessibility across a globally distributed edge infrastructure • Design, operate, and improve load balancing and traffic shaping systems at scale • Troubleshoot connection, latency, and accessibility issues end to end • Own HTTP traffic flow - from client to edge to origin and back • Investigate and resolve website and service reachability problems • Work across protocol layers to diagnose issues at the right depth