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Software Engineer (Technical Leadership

Job in Menlo Park, San Mateo County, California, 94029, USA
Listing for: Meta
Full Time position
Listed on 2026-08-02
Job specializations:
  • Software Development
    Full Stack Developer, Software Engineer, AI Engineer (Applied/Software), Software Architect
Salary/Wage Range or Industry Benchmark: 220000 - 320000 USD Yearly USD 220000.00 320000.00 YEAR
Job Description & How to Apply Below
Position: Software Engineer (Technical Leadership)

We are the teams who create all of Facebook’s product used by more than 1.5 billion people around the world. Want to build new features and improve existing products like Commerce, Ads, Video, Groups, News Feed, Search, and more? Want to solve unique, large scale, highly complex technical problems? Facebook is seeking experienced full‑stack software engineers to join our product teams.

You can help build products that help us connect the next billion people, create new features that have billions of interactions per day, and be a part of a team that’s working to help people connect around the globe.

Requirements
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Experience communicating and working across functions to drive solutions
  • Experience in mentoring/influencing engineers across organizations
  • 12+ years of experience with building large-scale applications, or similar experience
  • Proven track record of planning multi-year roadmap in which shorter-term projects ladder to the long-term vision
  • 8+ years of experience with web or mobile technologies
  • Experience leading projects with industry-wide impact
  • 12+ years of programming experience
  • Experience in driving large cross-functional/industry-wide engineering efforts
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • 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
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