Software Engineering Manager

Meta•Menlo Park, CA

4d•$219,000 - $301,000

About The Position

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.

Requirements

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

Nice To Haves

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)

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