Job Description

Meta is seeking a Software Engineering Manager to lead multiple teams of engineers and technical leaders delivering large-scale software systems. In this role, you will drive technical strategy, shape engineering roadmaps, and ensure high-quality execution across complex, high-impact projects. You will stay hands-on technically, leverage AI tools to expand your team's delivery capacity, and foster a culture of engineering craft, AI-nativeness, and cross-functional ownership. You will partner closely with product, design, and data science to build systems that serve billions of people worldwide.

Responsibilities

Manage multiple teams of engineers and technical leaders delivering on large-scale, high-impact software projects with multiple levels of dependencies

• Actively shape technical strategy and roadmap direction, using team-wide insights to set and prioritize longer-term engineering goals
• Stay technically engaged by using AI tools to evaluate technical direction, assess code quality, and contribute directly across teams
• Drive AI adoption within the team to expand delivery capacity and improve engineering workflows and tooling
• Proactively detect and resolve the largest execution challenges across teams, whether related to vision, strategy, technical direction, or people
• Build and grow the team by sourcing and closing candidates, developing technical leaders, and maintaining a high bar for performance including AI fluency
• Ensure org health by monitoring team sentiment, diagnosing issues, and taking proactive measures to maintain high retention and engagement
• Model cross-functional ownership by ensuring engineers engage substantively with product, design, and data partners rather than operating in silos
• Hold leaders accountable for managing performance, delivering constructive feedback, and maintaining engineering craft standards across the organization
• Represent the team's work and progress to broader organizational leadership, communicating risks, priorities, and implications of AI adoption clearly

Qualifications

8+ years of software engineering experience, including hands-on technical contribution

• 4+ years of engineering management experience, including managing teams with technical leaders or other managers
• Experience driving technical strategy and roadmap planning across multiple concurrent large-scale software projects
• Experience recruiting, developing, and retaining engineering talent, including performance management of leaders
• Experience partnering cross-functionally with product, design, and data science to define requirements and deliver software at scale Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adopting and scaling AI-assisted development tools and workflows across an engineering organization
• Experience building and shipping consumer-facing or infrastructure software systems at significant scale
• Track record of managing managers and developing engineering leaders in ambiguous, high-growth environments
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ability to influence technical direction and organizational priorities beyond direct team scope
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)