Software Engineer, Systems

Meta is seeking a Systems Software Engineer to design, build, and optimize the low-level infrastructure and platform software that powers Meta's products at massive scale. In this role, you will work on systems-level challenges spanning operating systems, runtime environments, networking stacks, storage infrastructure, or compute platform software. You will own the technical design and execution of complex systems components, drive engineering excellence across reliability, performance, and security, and partner closely with infrastructure, hardware, and product engineering teams to deliver foundational capabilities that enable Meta's services to operate efficiently and reliably at global scale.

Responsibilities

Design and implement systems-level software components including kernel interfaces, runtime systems, networking layers, storage subsystems, or platform services that operate at scale Own the technical architecture of systems projects from requirements definition through production deployment, including trade-off analysis, design documentation, and stakeholder alignment Profile and optimize critical code paths using instrumentation, tracing, and performance analysis tools to meet latency, throughput, and resource efficiency targets Build and maintain robust observability infrastructure including service level objectives, dashboards, alerting, and runbooks to ensure production reliability Investigate and resolve complex systems-level incidents, including non-reproducible bugs, race conditions, and multithreaded synchronization issues, and drive retrospective improvements Develop and enforce testing strategies including unit, integration, stress, and resiliency tests to prevent regressions and validate system behavior under failure conditions Drive cross-team technical initiatives by identifying dependencies, coordinating with partner infrastructure and platform teams, and unblocking execution across organizational boundaries Proactively incorporate privacy, security, and integrity principles into systems design, including threat modeling, access control, and secure data handling at the platform layer Mentor other engineers on systems design principles, debugging methodologies, and engineering best practices, and contribute to recruiting and technical program initiatives Identify and eliminate sources of technical debt, improve developer tooling and automation, and drive migrations that reduce legacy complexity across the systems codebase

Qualifications

6+ years of experience in systems software engineering, including work on operating systems, distributed systems, networking, storage, or low-level platform infrastructure 6+ years of experience writing production-quality code in systems programming languages such as C, C++, Rust, or Go Experience designing and owning the architecture of complex systems components, including evaluation of trade-offs across performance, reliability, and maintainability Experience with performance profiling, instrumentation, and optimization of systems-level code including memory management, concurrency, and I/O efficiency Experience building and operating production systems at scale, including incident response, root cause analysis, and reliability engineering practices Experience in large scale open web crawling ecosystem Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience contributing to open-source systems projects or publishing technical work related to operating systems, distributed systems, or platform infrastructure Experience with kernel development, hypervisor internals, container runtimes, or low-level networking protocols such as RDMA, DPDK, or eBPF Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience designing systems for high availability and fault tolerance, including overload protection, graceful degradation, and automated failover mechanisms Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience applying security hardening techniques at the systems level, including sandboxing, privilege separation, or secure inter-process communication