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Meta Logo Meta · IT - Software Development

AI Production Engineer

United States, Menlo Park 184000.00 - 257000.00 USD / Year · Job Posted February 16, 2026
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Job 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. As a AI Production Engineer on our AI Transformation team, you will apply this discipline to build and scale production-grade AI systems that enhance the productivity and experience of our executive leadership. This role is primarily a software and systems engineering role—you will spend the majority of your time writing high-quality code, designing resilient systems, building automation, and creating tooling that enables AI to run reliably and efficiently.

Job Responsibility

  • Design and implement production-grade AI/ML systems for executive productivity, including LLMs, RAG systems, agents, inference pipelines, and MLOps infrastructure
  • Write and review code, develop documentation and capacity plans, and debug the hardest problems, live, on complex AI systems serving executive leadership
  • Build automation, self-healing systems, and CI/CD pipelines to minimize manual intervention and operational toil
  • Own AI infrastructure—training, inference, data pipelines, and GPU fleet management—across cloud platforms (AWS, Azure, GCP) and Kubernetes
  • Set technical direction, lead design reviews, mentor engineers, and advise leadership on AI technology trends and trade-offs
  • Share an on-call rotation (~1 week per quarter) and serve as an escalation contact for critical AI system incidents
  • Champion reliability by design—building resilience into systems from the start with circuit breakers, fallbacks, and graceful degradation
  • Travel globally up to 20% of the year to engage with executive partners and scale business opportunities

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 7+ years of experience in Linux/Unix and network fundamentals
  • 7+ years of coding experience in an industry-standard language (e.g., Python, Go, C++, Java, Rust)
  • Experience with Internet service architecture, capacity planning, and handling needs for urgent capacity augmentation
  • Knowledge of common web technologies and Internet service architectures (CDN, load balancing, distributed systems)
  • Experience configuring and running infrastructure-level applications such as Kubernetes, Terraform, and cloud platforms (AWS, Azure, GCP)
  • Experience building and productionizing AI/ML systems, including LLMs, RAG architectures, inference optimization, and MLOps
  • Proven track record of leading complex technical initiatives and mentoring other engineers

Nice to have

  • BS or MS in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Background in Production Engineering, Platform Engineering, or Site Reliability Engineering (SRE)
  • Experience with GPU infrastructure, ML accelerators, and model serving at scale
  • Familiarity with observability tools (Prometheus, Grafana, Datadog) and database/caching technologies (MySQL, Redis, Memcached)

What we offer

  • bonus
  • equity
  • benefits
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