Job Description

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 - driving reliability, performance, and efficiency across Meta's production environment. You will own complex technical problems end-to-end, partnering with hardware, infrastructure, and product engineering teams to deliver systems that operate reliably at global scale.

Responsibilities

Design and implement systems-level software components including kernel interfaces, runtime libraries, networking subsystems, or storage layers that underpin Meta's production infrastructure

• Own the technical architecture of platform systems, evaluating trade-offs across performance, reliability, maintainability, and operational complexity
• Instrument and profile systems to identify performance bottlenecks, latency hotspots, and resource inefficiencies, then drive targeted optimizations with measurable impact
• Build and maintain robust observability infrastructure including service level objectives, dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
• Lead root cause analysis for complex, non-reproducible system failures including multithreaded race conditions, memory corruption, and kernel-level faults, and implement defensive programming patterns to prevent recurrence
• Drive reliability improvements by reducing single points of failure, designing safe rollout strategies, and conducting resiliency testing such as overload and fault injection exercises
• Collaborate with hardware and infrastructure teams to co-design systems software that takes advantage of new compute, memory, and networking capabilities
• Proactively incorporate privacy, security, and integrity principles into systems design, contributing back to shared frameworks and platform-level safeguards
• Mentor other engineers on systems design principles, debugging methodologies, and engineering best practices, and contribute to recruiting and technical program initiatives
• Drive cross-team technical alignment by authoring design documents, facilitating architecture reviews, and communicating trade-offs clearly to both technical and non-technical stakeholders

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

• 6+ years of experience in systems software engineering, including work on operating systems, runtime environments, distributed infrastructure, or low-level platform software
• Experience designing and owning the architecture of complex systems components, including evaluation of performance, reliability, and operational trade-offs
• Experience debugging complex systems-level issues such as memory management errors, concurrency bugs, kernel interactions, or network stack failures using advanced tooling and instrumentation
• Experience building and operating production systems at scale, including defining service level objectives, setting up monitoring and alerting, and leading incident response and retrospectives Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience optimizing systems for high-throughput or low-latency workloads, including profiling with tools such as perf, flamegraphs, or hardware performance counters
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience contributing to or maintaining open-source systems software projects
• Experience with kernel development, hypervisor internals, eBPF, or other low-level operating system interfaces
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience collaborating with hardware or silicon teams to co-design firmware, drivers, or platform software for custom compute or networking hardware