Software Engineer (Technical Leadership)

Meta is a technology company building platforms and products that help people connect and grow businesses. The Software Engineer (Technical Leadership) will guide technical direction, lead long-term cross-company initiatives, develop feature roadmaps, and collaborate with organizational leaders to improve engineering effectiveness and performance.

Responsibilities:

• Drive the team's goals and technical direction to pursue opportunities that make your larger organization more efficient
• Effectively communicate complex features and systems in detail
• Understand industry & company-wide trends to help assess & develop new technologies
• Partner & collaborate with organization leaders to help improve the level of performance of the team & organization
• Identify new opportunities for the larger organization & influence the appropriate people for staffing/prioritizing these new ideas
• Lead long term technical vision and roadmap for large cross-company efforts
• Suggest, collect and synthesize requirements and create an effective feature roadmap

Requirements:

• Vast experience communicating and working across functions to drive solutions
• 12+ years coding experience in C, C++, Java and/or C#
• 12+ years experience building server applications
• Experience in driving large cross-functional/industry-wide engineering efforts
• Proven track record of planning multi-year roadmap in which shorter-term projects ladder to the long term vision
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Experience leading projects with industry-wide impact
• Significant experience in mentoring/influencing engineers across organizations
• Experience with operating system internals, file systems, programming language design, or compilers
• 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