Production Engineer
Description
Production Engineers (PEs) at Meta are specialized software engineers who develop the underlying infrastructure for all of Meta's products and services, forming the backbone of every major engineering effort that keeps our platforms running smoothly and scaling efficiently. 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 experienced engineers across the organization, you’ll contribute to code and systems that go into production and are used by millions every day. In Production Engineering at Meta, we solve novel engineering problems daily — solving problems at a scale few others face.
Responsibilities
Own the end-to-end reliability and scalability of the platforms, services, and products built on top of Meta’s underlying infrastructure and network Write and review code, develop documentation and capacity plans, and debug the hardest problems, on some of the largest and most complex systems in the world Together with your engineering team, you will share an on-call rotation and be an escalation contact for live service incidents Partner with engineers across the organization on high-impact production systems, the code and systems you work on will be in production and used by billions of users all around the world
Qualifications
4+ years experience with software development, frameworks and APIs 4+ years experience coding in higher-level languages (e.g., PHP, Python, C++, Rust or Java) Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 4+ years of experience building, maintaining, and debugging production services/platforms such as cloud infrastructure, load balancers, relational databases, and messaging systems Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Depth of understanding in areas such as operating systems or TCP/IP network fundamentals Experience with distributed web-scale and data systems 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