Software Engineer, Systems

Meta
London, UK
6 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence C++ (Programming Language) Profiling Software Debugging Distributed Systems Reliability Engineering Software Engineering System Programming Computer Networking Systems Prompt Engineering Technical Debt

Job description

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., 1. Design and implement scalable, reliable systems infrastructure components spanning distributed computing, storage, networking, or runtime environments

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

Requirements

  1. 6+ years of experience in systems software engineering, including work on distributed systems, storage systems, networking infrastructure, or operating system-level components
  2. Experience designing and implementing large-scale, production systems with well-defined reliability, performance, and operational requirements
  3. Experience debugging complex, non-reproducible systems issues using advanced tooling such as profilers, static analyzers, tracing frameworks, or custom instrumentation
  4. Experience establishing observability for production systems through metrics, dashboards, alerting, and service level objectives
  5. Experience driving cross-team technical projects from design through production, including dependency coordination, staged rollout planning, and post-launch monitoring, 16. Familiarity with resiliency testing methodologies such as overload testing, chaos engineering, or fault injection for distributed systems
  6. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  7. Experience with systems programming languages such as C, C++, Rust, or Go in a production environment
  8. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  9. Experience contributing to platform or infrastructure projects that are consumed by multiple product or engineering teams
  10. Track record of improving developer productivity through tooling, automation, or codebase modernization efforts at an organizational scale
  11. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

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