Edison Scientific
Member of Technical Staff, Principal AI Infrastructure Engineer
$200K–$350K
San Francisco +2 · On-site · Principal · Full-time · Posted Sep 4, 2026
- Location
- San Francisco
New York
Boston - Experience
- 10+ years of professional infrastructure or platform engineering experience.
About the job
Designs, scales, and operates Kubernetes infrastructure that supports persistent AI scientist agents and other scientific workloads.
What you'll do
- Architect and operate highly available Kubernetes clusters for thousands of concurrent, persistent resources.
- Develop Kubernetes CRDs and operators to manage agent lifecycles, research pipelines, and long-running compute tasks.
- Lead infrastructure scaling, scheduling, observability, storage, networking, and incident response.
What they ask for
- 10+ years of professional infrastructure or platform engineering experience, including deep production Kubernetes expertise.
- Experience developing CRDs and Kubernetes operators and operating clusters with thousands of persistent or long-lived resources.
- Deep knowledge of Kubernetes internals and cloud infrastructure, networking, storage, and IAM.
- Proficiency in a systems or backend language; hands-on infrastructure-as-code and GitOps experience.
Nice to have
- Experience with data-intensive platforms, scientific computing, or ML/AI infrastructure.
- Startup or small-team experience with architectural ownership, or experience scaling through rapid growth.
Pay
$200K – $350K USD base salary
Tools
Kubernetes, Kubebuilder, Operator SDK, controller-runtime, AWS EKS, GCP GKE, Azure AKS, Terraform
AI focus
Builds and operates the infrastructure foundation for AI scientist agents performing long-running scientific research.
Model-written summary · the original posting is authoritative