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Software Engineer, Systems

Meta · Tel Aviv, Israel · London, UK

Spotted 2h ago

Job details

Level
Senior
Experience
6+ years
Posted
Oct 31, 2026
Last confirmed open
Oct 31, 2026

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Job description

About this role

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.

Responsibilities

  • Design and implement scalable, reliable systems infrastructure components spanning distributed computing, storage, networking, or runtime environments
  • Own end-to-end technical design for systems-level projects, evaluating architectural trade-offs and driving decisions that balance performance, reliability, and maintainability
  • Instrument systems with telemetry, dashboards, and alerting to establish visibility into performance bottlenecks, reliability regressions, and failure modes
  • Lead incident response and root cause analysis for production systems issues, authoring retrospectives and driving follow-up improvements to prevent recurrence
  • Define and enforce service level objectives for owned systems, building debugging runbooks and mitigation playbooks to reduce mean time to resolution
  • Collaborate with cross-functional partners across product engineering, infrastructure, and security to ensure systems designs meet privacy, security, and integrity requirements
  • Drive engineering efficiency by identifying development bottlenecks, building internal tooling and automation, and completing migrations that eliminate legacy technical debt
  • Mentor other engineers on systems design principles, coding standards, and operational best practices, and contribute to recruiting and technical program efforts
  • Analyze performance profiles using instrumentation and profiling tools to identify hotspots and drive targeted optimizations across the systems stack
  • Communicate technical decisions, trade-offs, and project status clearly to stakeholders across engineering levels and cross-functional roles

Qualifications

  • 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)
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