Software Engineer, Systems

Requirements

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

Preferred Qualifications

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

Responsibilities

• Architect and implement large-scale distributed systems and platform services that support high-throughput, low-latency workloads across Meta's product infrastructure
• Lead the technical design of systems components including storage layers, compute pipelines, networking abstractions, and service orchestration frameworks
• Identify and resolve systemic performance bottlenecks through instrumentation, profiling, and targeted optimization across the full systems stack
• Define and enforce service level objectives for owned systems, building dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
• Drive reliability improvements by reducing failure surface, designing resilient rollout strategies, and leading regular resiliency and overload testing exercises
• Collaborate with cross-functional partners across product engineering, infrastructure, and data science to align system architecture with evolving product and business requirements
• Establish and evolve coding standards, architectural patterns, and engineering best practices for systems development across the broader organization
• 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
• Mentor other engineers on systems design principles, debugging methodologies, and production operations, and contribute to onboarding programs for new team members
• Lead incident retrospectives, identify root causes of complex production failures, and drive implementation of systemic improvements to prevent recurrence