Production Engineer
Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Apr 17, 2024. Meta scores B on the Alion truth index.
PEs work across Meta’s product and infrastructure teams to ensure our services are reliable, performant, and capable of supporting billions of users. This means writing high-quality code, solving complex problems in live production, and tackling challenges that impact over 2 billion people worldwide.
Our PEs are embedded in teams across the spectrum - from products like Instagram, WhatsApp, Oculus, and Videos to critical backend services such as Storage, Cache, and Networking. The team brings together diverse levels of experience and backgrounds.
Working alongside some of the best engineers in the industry, you’ll contribute to code and systems that go into production and are used by millions every day. In Production Engineering at Meta, we navigate uncharted waters daily - solving problems at a scale few others face.
Responsibilities
Own back-end services like our container fleet management systems, front-end services like Chat and Newsfeed, infrastructure components like our Memcache infrastructure, and everything in between Write and review code, develop documentation and capacity plans, and debug the hardest problems, live, on some of the largest and most complex systems in the world Together with your engineering team, you will share an on-call rotation Partnered alongside the best engineers in the industry on the coolest stuff around, the code and systems you work on will be in production and used by millions of users all around the world
Qualifications
Experience learning software, frameworks and APIs Engineering degree, or a related technical discipline, or equivalent work experience Experience in configuration and maintenance of applications such as web servers, load balancers, relational databases, storage systems and messaging systems Experience coding in higher-level languages (e.g. Python, Rust, PHP, C++) BS or MS in Computer Science 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