Hyperscale Cloud Production Systems Engineer - Equity

Meta; Temple (TX); On-site; USD 173,000 - 245,000; Full time

Job summary

Meta is seeking an experienced Cloud Production Systems Engineer to join the Data Center Operations team. You will analyze telemetry, develop automation tooling, and drive resilient cloud infrastructure across our hyperscale data centers.

You will collaborate with global teams, own diagnostic tooling, and mentor others while traveling up to 25% to support new site deployments and fleet health initiatives. The role requires deep data analysis, strong coding skills in Python and other languages,

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 7+ years of experience in production systems engineering, infrastructure engineering, or system software development for large-scale cloud environments
• 7+ years of experience with hardware lifecycle management, fleet automation, or cloud data center operations systems spanning compute, storage, or networking infrastructure
• Experience developing systems software or automation tooling in Python, Bash, PHP, C, or C++ for Linux-based production environments at scale
• Experience with the configuration and maintenance of production systems, including web servers, load balancers, relational databases, storage systems, and messaging systems
• Experience communicating technical designs and cloud infrastructure decisions through written documentation and cross-functional stakeholder alignment across engineering and operations teams

Responsibilities

• Identify and root cause systemic issues across the cloud server fleet and drive resolutions to maximize uptime and utilization by leveraging hardware failure data and diagnostic telemetry
• Write, review, and maintain code for diagnostic and cloud automation tooling that supports quality and efficient delivery of production servers at hyperscale
• Own and develop diagnostic tooling requirements that enable frontline operations teams to efficiently manage and repair the cloud server fleet
• Drive the escalation process for Data Center Operations to identify, root cause, and resolve complex cloud tooling and hardware issues affecting fleet health
• Execute operational validation and verification activities for new cloud product integration into the production environment
• Collaborate with cross-functional cloud tooling teams to provide an operations-centric perspective on open issues and contribute to their development roadmaps
• Perform deep data analysis to prioritize cloud automation opportunities for server repair workflows in a large-scale, heterogeneous hardware environment
• Build cross-functional relationships and influence policies and procedures to improve global cloud data center operations consistency and efficiency
• Mentor other engineers on evaluating and resolving cloud fleet issues and defining improvements to tools and operational processes
• Travel up to 25% to support global cloud data center operations and new site deployments

Education

Bachelor's degree in Computer Science/Computer Engineering or equivalent

7+ years in production systems engineering or large-scale cloud environments

7+ years with hardware lifecycle management or fleet automation

Experience with systems programming languages (Python, Bash, C, C++, PHP) for Linux production environments

Experience with production systems (web servers, load balancers, databases, storage, messaging)

Experience communicating designs and cloud infra decisions through docs and cross-functional alignment

Tools

Python

Bash

PHP

C

C++

Job description

Meta is seeking an experienced Cloud Production Systems Engineer to join the Data Center Operations team. You will analyze telemetry, develop automation tooling, and drive resilient cloud infrastructure across our hyperscale data centers.

You will collaborate with global teams, own diagnostic tooling, and mentor others while traveling up to 25% to support new site deployments and fleet health initiatives. The role requires deep data analysis, strong coding skills in Python and other languages,