Meta
Software Engineer, Infrastructure (Technical Leadership) - Central Security
$219K–$301K
Menlo Park, CA +1 · Remote · Full-time · Posted Oct 22, 2026
- Location
- Menlo Park, CA
Remote, US - Experience
- 12+ years of programming experience in a relevant language OR 8+ years experience with a PhD; also asks for 8+ years relevant experience building large-scale infrastructure applications or similar experience.
- Education
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
About the job
Leads technical direction and long-term infrastructure efforts for Central Security, building AI/ML-enabled security systems and addressing security risks across products and infrastructure.
What you'll do
- Set technical direction and lead long-term roadmaps for large cross-company efforts.
- Develop automated and autonomous security systems using AI/ML and help identify and mitigate security risks across AI/ML systems.
- Drive cross-functional engineering initiatives, resolve performance and scalability issues, and reduce technical debt.
What they ask for
- 12+ years of programming experience in a relevant language OR 8+ years experience with a PhD.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- 8+ years relevant experience building large-scale infrastructure applications or similar experience.
- Experience leading cross-functional engineering efforts, planning multi-year roadmaps, and using data to explain technical problems and solutions.
Nice to have
- Demonstrated curiosity about security, such as reasoning about failure modes, abuse cases, or threat models; prior formal security experience is not required.
- Demonstrated ability to integrate AI tools, apply responsible AI practices, and develop AI skills such as prompt/context engineering or agent orchestration.
Pay
$219,000/year to $301,000/year (base salary)
Tools
AI/ML, C, C++, Java, Python, Javascript, Hack
AI focus
Build AI/ML-enabled security systems; address security risks across classical ML, agentic product features, and frontier models; integrate AI tools into workflows and apply responsible AI practices.
Model-written summary · the original posting is authoritative