Software Engineer - Backend Infrastructure, Standalone Apps Team

We're Meta's Standalone Apps Team — we build new apps to reach new user scenarios and serve needs that aren't well met today. The project we're building right now is an image-and-text community where real people share first-hand experiences and recommendations — what to try, where to go, how to do something. It's where people come to get inspired and to make everyday decisions, learning from others who've actually been there. It's still early — a small team working 0→1. If you want high ownership, a short path from idea to ship, and the chance to shape a product from its first version, this is that kind of team. We're looking for a senior infrastructure engineer to build the platform the product runs on. You'll own the foundations — data pipelines, storage, service frameworks, and developer tooling — that let a small team move fast without breaking things.

Responsibilities

• Design, build, and own core infrastructure: data pipelines, storage, service frameworks, and deployment/observability tooling.
• Make the platform reliable, scalable, and cost-efficient; remove bottlenecks before they slow the team down.
• Set technical direction for infra; define the patterns product engineers build on.
• Partner with product and ML engineers to support their throughput and reliability needs.
• Mentor other engineers and raise the operational bar.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 12+ years of software engineering experience, with significant time on infrastructure, platform, or distributed systems
• Deep grasp of distributed systems, storage, reliability, and performance
• Track record of building and operating infrastructure at scale
• Experience leading technical direction and working independently with limited guidance 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
• Experience standing up infrastructure for a new product (0→1)
• Experience with large-scale data systems, ML infrastructure, or developer-productivity tooling