Principal AI Reliability Engineer

Meta

Montpelier (VT)

On-site

USD 271,000 - 347,000

Full time

41 hours ago
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Job summary

Meta seeks an experienced Software Engineer to build AI systems for production reliability. You will prototype, ship, and operate an autonomous AI agent for incident investigation and mitigation at Meta scale, with human oversight.

The role combines large-scale distributed systems, observability, and applied AI, requiring practical engineering and judgment to move ideas to production safely. You will partner across infrastructure, AI, product, and reliability teams to improve agent capabilities

Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 12+ years of software engineering experience, including experience building and operating large-scale distributed or infrastructure systems
  • Experience setting technical direction and leading complex, multi-year engineering efforts across organizational boundaries
  • Experience applying AI or machine learning systems to production problems
  • Demonstrated experience moving from technical concept to production deployment and measurable impact
  • Experience diagnosing complex production systems using telemetry, code, configuration, and dependency information
  • Experience coding in languages such as C++, Java, Python, Rust, or equivalent
  • Recent hands‑on experience building and shipping complex production systems, with the ability to move directly between architecture, experimentation, debugging, and implementation
  • Experience influencing senior engineers and leaders without direct organizational authority

Responsibilities

  • Define the technical vision and architecture for agentic reliability systems across Meta
  • Personally design, code, and ship production agentic systems for complex infrastructure problems
  • Lead the development of an AI agent for production incident investigation and mitigation, advancing it toward accurate, trusted, and safely supervised autonomous action
  • Develop major improvements in agent reasoning, context, tool use, planning, evaluation, learning, and safe execution
  • Explore and apply techniques including automated hill climbing, fine-tuning, reinforcement learning, model routing, distillation, pruning, and inference optimization, selecting the simplest approach that produces measurable gains
  • Identify new high-value applications of AI across incident prevention, detection, mitigation, observability, and infrastructure operations
  • Move rapidly from ambiguous problems to prototypes, validate them against real production workloads, and develop successful approaches into reliable systems at scale
  • Build evaluation and experimentation systems that connect agent quality to outcomes such as investigation accuracy, successful mitigation, incident duration, and reduced operational work
  • Build closed-loop improvement systems that turn production outcomes into evaluations, experiments, and better agent behavior
  • Establish architectures and guardrails for production actions, including authorization, independent validation, auditability, rollback, and human oversight
  • Partner with Infrastructure, AI, Product, and Reliability leaders to integrate agentic capabilities into Meta’s production ecosystem
  • Influence technical strategy across organizations and mentor other engineers working on distributed systems and applied AI

Skills

Distributed systems
Production reliability
AI integration
C++/Java/Python
Mentoring engineers
Incident response
Autonomous systems

Job description

Meta seeks an experienced Software Engineer to build AI systems for production reliability. You will prototype, ship, and operate an autonomous AI agent for incident investigation and mitigation at Meta scale, with human oversight.

The role combines large-scale distributed systems, observability, and applied AI, requiring practical engineering and judgment to move ideas to production safely. You will partner across infrastructure, AI, product, and reliability teams to improve agent capabilities

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