> Markdown version of [/jobs/ext/4135288-software-engineering-manager-wearables-infra](https://www.wearedevelopers.com/jobs/ext/4135288-software-engineering-manager-wearables-infra). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineering Manager, Wearables Infra - **Company:** Facebook Inc. - **Location:** New York, NY, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Augmented Reality, Automation of Tests, Software Quality, Distributed Systems, Release Management, Software Engineering, Prompt Engineering, Wearables, Automation Anywhere - **Published:** October 12, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28101695/Software-Engineering-Manager-Wearables-Infra-New-York-New-York-7418 ## About the Role * 8+ years of software engineering experience in systems, infrastructure, distributed systems, or related technical domains * 5+ years of engineering management experience, including managing teams delivering large-scale systems projects operating at high scale and reliability * 2+ years of experience in managing other engineering managers or technical leaders * Experience driving technical strategy and roadmap decisions for complex, high-scale systems with multiple layers of dependency * Experience building and operating systems for reliability, availability, and performance -- setting and holding quality bars (SLAs/SLOs) as scope and load grow * Experience scaling infrastructure, teams, and processes to keep pace with rapidly growing product and developer demand * Experience in recruiting, developing, and retaining engineering talent, including managing performance and building team health Preferred Qualifications: * Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) * Experience partnering with product and data science organizations to co-define systems requirements and deliver infrastructure that directly enables product outcomes * Track record of integrating AI tools and workflows into engineering team practices to measurably improve delivery capacity and code quality * Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) * Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies * Demonstrated ability to build and scale engineering organizations through periods of significant technical or organizational ambiguity ## Description Meta Reality Labs is seeking a Software Engineering Manager to lead the productivity and systems infrastructure behind Meta's fastest-growing product category: AI-powered wearables. On the heels of Ray-Ban Meta AI glasses becoming one of the most popular consumer devices in Meta's history, we are scaling to a broad next-generation portfolio of smart glasses, wrist wearables, and augmented reality devices. You will manage teams building the large-scale, high-reliability infrastructure that keeps 2,000+ wearable developers fast and unblocked -- mainline health, build and release, test automation, on-demand devices and emulators, and developer tooling -- while driving technical strategy, championing AI-assisted engineering workflows, and partnering across product, QA, and data science to ship systems that are fast, resilient, and built to scale., * Manage teams of engineers and technical leaders who deliver large-scale infrastructure with significant cross-org dependencies * Shape the technical strategy and roadmap for the productivity and systems infrastructure powering our wearables portfolio * Stay hands-on, evaluating architecture, reviewing system designs, and contributing directly with AI-assisted tools * Partner with product, hardware, QA, and data science to keep teams engaged substantively, not siloed * Proactively surface and resolve execution risks across vision, strategy, and people to keep teams from being unblocked * Foster strong engineering craftsmanship through investment in AI workflows and tooling * Monitor organization health through regular feedback loops, pulse data, and structured development conversations