Software Engineer, Systems

Meta is seeking a Staff Systems Software Engineer to design and build the foundational infrastructure that powers products used by billions of people worldwide. In this role, you will architect and implement large-scale distributed systems, low-level platform components, and high-performance services that underpin Meta's core product stack. You will drive technical strategy across system reliability, performance, and scalability, partnering closely with product, infrastructure, and data engineering teams to deliver systems that operate at global scale with high availability and efficiency., 1. Architect and implement large-scale distributed systems and platform services that support high-throughput, low-latency workloads across Meta's product infrastructure
2. Lead the technical design of systems components including storage layers, compute pipelines, networking abstractions, and service orchestration frameworks
3. Identify and resolve systemic performance bottlenecks through instrumentation, profiling, and targeted optimization across the full systems stack
4. Define and enforce service level objectives for owned systems, building dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
5. Drive reliability improvements by reducing failure surface, designing resilient rollout strategies, and leading regular resiliency and overload testing exercises
6. Collaborate with cross-functional partners across product engineering, infrastructure, and data science to align system architecture with evolving product and business requirements
7. Establish and evolve coding standards, architectural patterns, and engineering best practices for systems development across the broader organization
8. Leverage AI-assisted development workflows to accelerate design iteration, code generation, and systems analysis, applying sound judgment on when to rely on AI versus deep systems expertise
9. Mentor other engineers on systems design principles, debugging methodologies, and production operations, and contribute to onboarding programs for new team members
10. Lead incident retrospectives, identify root causes of complex production failures, and drive implementation of systemic improvements to prevent recurrence

11. 8+ years of experience designing and implementing large-scale distributed systems, platform infrastructure, or systems software in production environments
12. Experience leading major technical initiatives end-to-end, including architecture design, cross-team coordination, staged rollout, and post-launch reliability ownership
13. Experience debugging complex, non-reproducible systems issues including concurrency bugs, memory management failures, and distributed consistency problems
14. Experience defining service level objectives, building observability infrastructure, and driving reliability improvements across production systems
15. Experience communicating technical architecture decisions and trade-offs in writing to both engineering and non-engineering stakeholders

Preferred Qualifications:

Preferred Qualifications:
16. Experience with systems programming languages such as C, C++, or Rust in the context of high-performance or low-latency infrastructure
17. Experience building or improving developer tooling, automation frameworks, or internal platforms that measurably improve engineering efficiency across teams
18. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
19. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
20. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
21. Experience designing or contributing to storage systems, compute scheduling frameworks, or inter-service communication protocols at scale
22. Demonstrated use of AI tools to accelerate systems design, automate operational workflows, or improve code quality and test coverage