Software Engineer, Systems

Meta is seeking a Software Engineer to design, build, and scale the foundational systems infrastructure that powers products used by billions of people worldwide. In this role, you will work across the systems stack — spanning distributed systems, storage, networking, runtime environments, and platform services — to deliver reliable, high-performance infrastructure that enables product teams to move quickly and safely at scale. You will own technical design and execution across complex, cross-cutting systems projects, partnering closely with engineers across the organization to drive engineering excellence and long-term platform health.

• 6+ years of experience in systems software engineering, including work on distributed systems, storage systems, networking infrastructure, or operating system-level components
• Experience designing and implementing large-scale, production systems with well-defined reliability, performance, and operational requirements
• Experience debugging complex, non-reproducible systems issues using advanced tooling such as profilers, static analyzers, tracing frameworks, or custom instrumentation
• Experience establishing observability for production systems through metrics, dashboards, alerting, and service level objectives
• Experience driving cross-team technical projects from design through production, including dependency coordination, staged rollout planning, and post-launch monitoring
• Familiarity with resiliency testing methodologies such as overload testing, chaos engineering, or fault injection for distributed systems
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience with systems programming languages such as C, C++, Rust, or Go in a production environment
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience contributing to platform or infrastructure projects that are consumed by multiple product or engineering teams
• Track record of improving developer productivity through tooling, automation, or codebase modernization efforts at an organizational scale
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)