Principal AI Reliability Engineer for Production Autonomy

Meta; Columbus (OH); On-site; USD 271,000 - 347,000; Full time

Job summary

Meta is seeking an experienced Software Engineer to build the next generation of AI systems for production reliability. You will lead the development of an AI agent that autonomously investigates production incidents, identifies root causes, and creates safe mitigation plans under human supervision.

This role sits at the intersection of large-scale distributed systems, incident response, and applied AI, requiring hands-on coding across architecture, experimentation, and deployment at Meta scale.

Qualifications

• Bachelor's degree or equivalent practical experience in CS/Engineering or related field.
• 12+ years of software engineering experience with large-scale distributed or infrastructure systems.
• Experience leading complex multi-year engineering efforts across teams.
• Experience applying AI or ML to production problems.

Responsibilities

• Define the technical vision and architecture for agentic reliability systems at Meta.
• Design, code, and ship production agentic systems for complex infrastructure problems.
• Lead development of an AI agent for production incident investigation and mitigation.
• Improve agent reasoning, context, tool use, planning, evaluation, learning, and safe execution.
• Explore techniques like fine-tuning, reinforcement learning, distillation, and inference optimization.

Education

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Tools

C++

Java

Python

Rust

Job description

Meta is seeking an experienced Software Engineer to build the next generation of AI systems for production reliability. You will lead the development of an AI agent that autonomously investigates production incidents, identifies root causes, and creates safe mitigation plans under human supervision.

This role sits at the intersection of large-scale distributed systems, incident response, and applied AI, requiring hands-on coding across architecture, experimentation, and deployment at Meta scale.