Own the platform: GCP, Kubernetes, Temporal, GPU fleet, deploy and rollback machinery
Build AI enablement substrate: GPU capacity, training/inference pipelines, serving costs
Treat cost as an engineering constraint
Ensure security: identity, access, secrets, least-privilege, supply chain
Make systems legible: infrastructure-as-code, runbooks, observability
Improve team learning and shipping practices

🎯 Requirements

8+ years building and operating production distributed systems
Leverage agents to multiply impact and think critically about AI use
Experience running systems where failure was expensive
Carried a pager, commanded incidents, and rolled back
Use SLOs and error budgets as operating tools
Experience with a major cloud provider and Kubernetes in production

🎁 Benefits

Generous healthcare package
401k matching program
Catered lunches
Flexible vacation time
Equity

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