Software Engineer, Front End
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Get Started FreeAbout interviewing at Meta
Recruiter screen, a technical screen (60-minute asynchronous challenge or paired live coding), a short culture-fit questionnaire, then a virtual onsite of about four rounds: fast-paced coding with multiple problems per round, system design scoped to level, a lighter behavioral, and an AI-enabled coding round assessing how you work with a coding assistant.
Read the full Meta interview process →Description
About
Meta is seeking a Staff Software Engineer to help shape the future of JavaScript tooling and developer infrastructure across Meta's family of products. In this role, you will design and implement JS compiler enhancements, build and improve developer tools such as linters and test runners, and integrate LLM-powered capabilities into developer workflows. You will drive the architecture and technical direction of JS tooling systems that empower thousands of engineers to build faster, safer, and more efficiently at scale.
Responsibilities
- Lead the design and implementation of compiler passes and JavaScript transformations that improve code quality, performance, and developer experience across Meta's codebase
- Build and enhance developer tooling infrastructure including linters, test runners, and code analysis tools used by thousands of engineers
- Integrate LLM-powered capabilities into developer workflows, accelerating code generation, automated fixes, and intelligent tooling assistance
- Drive end-to-end delivery of major JS tooling initiatives, coordinating dependencies across engineering, product, and infrastructure teams
- Identify and resolve complex performance bottlenecks in build systems, bundlers, and JavaScript execution to ensure fast developer feedback loops
- Establish and evolve best practices for JavaScript tooling, including AST manipulation, static analysis, and incremental compilation strategies
- Mentor other engineers on compiler design, tooling architecture, and AI-assisted development practices
- Partner with cross-functional stakeholders to independently drive technical decisions and roadmap priorities for developer tools
- Proactively identify and address technical debt in tooling infrastructure, lead migrations to modern standards, and ensure maintainability at scale
- Communicate technical strategy, trade-offs, and roadmap decisions clearly to both engineering and non-engineering audiences, including leadership
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 8+ years of experience in front-end software engineering, including JavaScript, HTML, and CSS
- Experience leading and delivering major front-end initiatives involving complex system architecture, cross-team coordination, and phased rollouts
- Experience designing and building scalable, performant, and accessible user interface systems for products with large user bases
- Experience using data, experimentation frameworks, and telemetry to drive front-end product and engineering decisions
- Experience communicating technical decisions and trade-offs in writing to both technical and non-technical stakeholders Experience with modern front-end frameworks such as React, including deep knowledge of rendering performance, state management, and component lifecycle
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Experience integrating AI tools into front-end development workflows to drive measurable gains in engineering efficiency or product quality
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience with browser performance profiling, Core Web Vitals optimization, and progressive enhancement techniques for diverse device and network conditions
- Experience building and maintaining design systems or shared component libraries used across multiple product teams
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)