Software Development Engineer in Test
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Before you apply
Salary$173k – $237k
LocationMenlo Park, CA; Seattle, WA
Typefull-time
SeniorityLead
Experience8+ yrs
DepartmentInstagram, Messenger, Facebook
EquityIncluded
Company size10,000+ people
PostedOct 12, 2026 · 3w ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
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 quality strategy and engineering decisions to both technical and non-technical stakeholders through written proposals and cross-functional alignment
Demonstrated history of influencing engineering culture and practices at an organizational level through tooling, standards, or enablement programs
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
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
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
Skills
Python
React
AWS
PostgreSQL
About the role
Meta is seeking a Staff Software Development Engineer in Test to define and lead quality engineering strategy across Meta’s large-scale, distributed software systems and products. In this role, you will architect test infrastructure, establish organization-wide quality standards, and drive systemic improvements to reliability, coverage, and release confidence across multiple engineering organizations. You will operate at the intersection of product engineering, platform infrastructure, and developer productivity, shaping how quality is built into software at every stage of the development lifecycle.
Responsibilities
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Define and own the long-term quality engineering strategy and test architecture for large-scale distributed systems spanning multiple product areas and engineering organizations
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Design and build scalable, reusable test automation frameworks and infrastructure that can be adopted broadly to improve reliability, coverage, and developer productivity
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Lead cross-functional quality initiatives by partnering with product engineering, platform, and infrastructure teams to identify systemic quality gaps and drive resolution at the root cause level
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Establish and evangelize standards for test design across unit, integration, end-to-end, performance, and fault-injection testing methodologies
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Develop and own quality metrics, dashboards, and reporting systems that provide actionable signal on product health, test coverage, and release readiness
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Evaluate and improve CI/CD pipeline quality gates, staged rollout validation processes, and feature flagging strategies to reduce production incidents and improve deployment confidence
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Identify systemic reliability, scalability, and performance issues through root cause analysis and drive proactive improvements to test coverage and signal fidelity
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Mentor and provide technical guidance to other engineers across quality and product engineering teams, elevating the overall test engineering craft across the organization
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Influence engineering roadmaps and architectural decisions by advocating for testability, observability, and quality as first-class engineering requirements
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Drive adoption of quality engineering practices across the organization through documentation, tooling, and cross-team enablement programs
Minimum qualifications
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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 quality strategy and engineering decisions to both technical and non-technical stakeholders through written proposals and cross-functional alignment
Preferred qualifications
•
Demonstrated history of influencing engineering culture and practices at an organizational level through tooling, standards, or enablement programs
•
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
•
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
•
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