Senior Reliability & AIOps Leader

LAM RESEARCH Corporation

Fremont (CA)

On-site

USD 137,000 - 287,000

Full time

7 days ago

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Job summary

Lam Research in the San Francisco Bay Area is seeking a Senior Manager of Reliability Engineering & AIOps to lead a global team that keeps critical infrastructure running and ready for the next failure. You will define service level objectives, own disaster recovery and incident management, and guide AI-powered automation to reduce outages and toil.

You will collaborate across Azure, AWS, GCP, and on‑prem environments, shaping cross‑regional capabilities and a culture of blameless postmortems

Qualifications

Bachelor's degree in Computer Science, Engineering, or related field with 10 years of related experience; or a Master's with 8 years.
Proven experience leading reliability or operations teams and setting technical direction.
Incident command experience on major outages and postmortem ownership.
Deep disaster recovery planning across Azure, AWS, GCP, and core infra.
Hands-on ownership of incident management and paging platforms (e.g., PagerDuty).
Experience with capacity planning, performance trending, and demand forecasting for global production environments.
Strong observability tooling knowledge (Prometheus, Grafana, Loki, Tempo).
Infrastructure as code (Terraform) and scripting in Python or Go.
Experience applying AI-assisted engineering and operations tools with guardrails for security and safety.

Responsibilities

Lead, hire, and develop the reliability engineering team, owning on-call health while staying technically hands-on.
Set the reliability strategy: define SLO program, publish error-budget policy, drive adoption across teams.
Build and run a follow-the-sun on-call and response model across six regions with consistent runbooks.
Own incident management and paging end-to-end, including schedules, escalation policies, and routing as code.
Serve as incident commander on major incidents, communicate with executives, and lead blameless postmortems.
Own disaster recovery strategy across cloud and core infrastructure, with RO, backup, and DR exercises.
Lead capacity planning and performance engineering across cloud and HPC platforms.
Define and drive AI Ops requirements across Azure, AWS, GCP, and hybrid infra.
Participate in global on-call rotation and continuous improvement of reliability practices.