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Salary
≈ $170k – $331k per year (Estimated)
Location
In office (Menlo Park)
Seniority
Staff · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Sep 9, 2026. Meta scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Meta Platforms is an American technology company founded in 2004 as Facebook and renamed in 2021 to signal its investment in immersive computing. It operates the largest family of social and messaging applications in the world, comprising Facebook, Instagram, WhatsApp, Messenger and Threads, and earns almost all of its revenue from advertising sold against that audience. Headquartered in Menlo Park, California, the company also develops the open Llama language models and the Reality Labs division behind Quest headsets and Ray-Ban smart glasses.
Meta is seeking a Staff Software Development Engineer in Test to drive quality engineering strategy across large-scale software systems and products. In this role, you will define and lead the test engineering vision for complex, distributed systems, establishing frameworks, tooling, and methodologies that raise the quality bar across multiple product areas and engineering organizations. You will partner with product, infrastructure, and platform engineering teams to embed quality practices at every stage of the software development lifecycle, from design through production.

Responsibilities

Define and drive the long-term quality engineering strategy and test architecture for large-scale, distributed software systems across multiple product areas Design and build scalable test automation frameworks, infrastructure, and tooling that can be adopted organization-wide to improve reliability and coverage Lead cross-functional quality initiatives by partnering with product engineering, infrastructure, and platform teams to identify systemic quality gaps and drive resolution Establish standards and best practices for test design, including unit, integration, end-to-end, performance, and chaos/fault-injection testing methodologies Develop and own quality metrics, dashboards, and reporting systems that provide actionable signal on product health, test coverage, and release readiness Evaluate and improve CI/CD pipeline quality gates, staged rollout validation processes, and feature flagging strategies to reduce production incidents Identify and resolve systemic reliability, scalability, and performance issues through root cause analysis and proactive test coverage improvements Mentor and provide technical guidance to other engineers across quality and product engineering teams, elevating overall test engineering craft Influence engineering roadmaps and architectural decisions by advocating for testability, observability, and quality as first-class engineering requirements Drive adoption of quality engineering practices across the organization through documentation, tooling, and cross-team enablement programs

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of experience in software development engineering in test, quality engineering, or software engineering with a focus on test infrastructure and automation Experience designing and implementing large-scale test automation frameworks and CI/CD quality pipelines for distributed systems Experience defining quality strategy and driving adoption of testing methodologies across multiple engineering teams or product areas Experience with performance testing, reliability engineering, or fault-injection testing for high-scale production systems Experience communicating technical quality strategy and engineering decisions to both technical and non-technical stakeholders through written proposals and cross-functional alignment Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience with observability platforms, production monitoring, and using telemetry data to inform test coverage and quality signal Experience applying static analysis, fuzzing, or model-based testing techniques to improve defect detection in complex software systems Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience building test infrastructure and quality tooling that spans mobile, web, and backend systems within a single product ecosystem Demonstrated history of influencing engineering culture and practices at an organizational level through tooling, standards, or enablement programs

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