Software Engineer, Principal

About

Meta is seeking a principal-level software engineer to drive technical strategy and engineering excellence across large-scale product systems. You will join XF APAC Products, an AI-first team leading commercial monetization, consumer app experimentation, and AI for Business This team is redesigning Meta's product development workflows for greater speed and efficiency. You will define architectural direction, lead multi-year technical initiatives, and set the standard for AI-native engineering practices across Meta's product portfolio.

Responsibilities

• Define and drive multi-year technical vision and architecture for critical product systems, ensuring designs are reliable, extensible, and built to scale across Meta's global infrastructure
• Identify and lead transformative engineering initiatives that fundamentally improve product quality, system performance, or developer efficiency at the organizational level
• Establish extensible technical foundations and coding standards that promote consistency across multiple engineering organizations and product platforms
• Develop and champion AI-native engineering workflows that serve as force multipliers for cross-disciplinary teams, enabling broader scope and faster iteration
• Diagnose and resolve the most complex systemic technical problems spanning multiple systems and abstraction layers, generalizing solutions to prevent entire classes of issues
• Collaborate with product, design, data science, and operations partners to define strategic priorities, align on technical trade-offs, and drive execution across cross-functional teams
• Mentor engineers across the organization by providing candid technical guidance, customized coaching, and frameworks for navigating ambiguous, high-stakes engineering decisions
• Define new metrics and data-driven decision-making principles for long-term, cross-team projects and connect them to organization-level priorities
• Influence technical design in adjacent engineering areas, conducting rigorous architecture reviews and ensuring cohesion across component interfaces and data flows
• Lead engineering programs and process improvements that raise the bar for reliability, privacy, security, and product quality across the broader engineering community

Minimum Qualifications

• 12+ years of software engineering experience in large-scale product systems, including architecture design, systems reliability, and cross-organizational technical leadership
• Experience defining and delivering multi-year technical roadmaps that balance short-term execution with long-term architectural integrity across multiple engineering teams
• Experience identifying and resolving systemic technical problems that span multiple systems, including developing invariants and approaches that prevent entire categories of issues
• Experience influencing technical strategy and priorities across multiple engineering organizations and cross-functional partners through written proposals, design reviews, and stakeholder alignment
• Experience applying AI tools and workflows to accelerate engineering productivity, expand technical scope, and drive step-change improvements in system design or product outcomes Experience leading large-scale system migrations or platform renewals in complex, mature technical environments with significant cross-team dependencies
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Track record of industry-level impact in a specific technical domain, including contributions that have influenced engineering practices beyond a single company
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience establishing engineering standards, architectural patterns, or technical frameworks that have been adopted broadly across large engineering organizations
• Experience defining and operationalizing reliability, privacy, or security practices at the ecosystem level, including partnering with legal, policy, and compliance teams on technical solutions