SpaceX Sr. Security Engineer (Infrastructure) at SpaceX designs and manages on-premises Kubernetes platforms for security services. Leads cluster lifecycle, automation, and hardening to protect enterprise systems.
Responsibilities
Design on-premises Kubernetes platforms that security services run on, and the compute, storage, and networking they depend on.
Lead cluster lifecycle work, including upgrades, capacity, failure domains, and safe change.
Build the automation other engineers use to provision, configure, and operate the platform.
Set standards for how security services are deployed, hardened, and run on Kubernetes.
Harden clusters and workloads, including RBAC, policy, secrets, and secure configuration.
Respond to the hardest production incidents and drive them to a durable fix.
Define the signals, alerts, and operational practices that keep the platform supportable.
Document what you run, keep it working, and advise other teams on it.
Find systemic gaps with security and IT, then ship platform and deployment changes that reduce risk.
Deliver solutions that are scalable, repeatable, maintainable, and secure.
Coordinate with information security, IT, software, and other partners.
Qualification
Production Kubernetes at scaleDesigning on-premises computeCluster and node hardeningLinux internals and troubleshootingObservability
Required
Bachelor's degree in computer science or another STEM discipline; OR 2+ years of professional experience operating production infrastructure and high school diploma or equivalency certificate in lieu of a degree.
5+ years of experience operating on-premises Kubernetes in a production environment.
5+ years of experience with Linux system administration and with Python, Go, or another language used to automate infrastructure.
Preferred
Production Kubernetes at scale, including control plane, networking, storage, RBAC, and upgrades.
Designing on-premises compute, storage, and network architectures for container platforms.
Cluster and node hardening, admission control, and secure workload configuration.
Infrastructure as code and configuration management.
Python or Go for platform tooling and automation.
Linux internals and troubleshooting.
Observability, alerting, and operational readiness for production platforms.
