Infrastructure Engineer; Kubernetes Specialist
Listed on 2026-10-18
-
Software Development
Cloud Engineer - Software, DevOps
About Type Safe
We're building prod, not god. Type Safe is an AI lab pushing frontier model intelligence in a new direction, starting with System One Models. We combine the reasoning of LLMs with the reliability of code, for truly trustworthy AI. Our first model, Jev, launched in September 2026.
While others chase leaderboards, we're rebuilding the LLM stack from first principles to make models smarter and also dependable enough to run in production. We're a small, fast team backed by an $870M Series A led by a16z. Made in SF, with love. Come join the frontier.
About the roleWe're looking for an Infrastructure Engineer to build and operate the infrastructure behind Type Safe AI's products at global scale. You'll own the systems that serve millions of users across regions - from provisioning Kubernetes clusters across multiple clouds to optimizing networking for low-latency AI inference.
This is a high-impact role on a small, fast-moving team. You'll work across the full infrastructure stack: cloud primitives, container orchestration, networking, observability, and the specialized infra that makes large-scale model inference efficient.
What you'll doDesign, deploy, and operate Kubernetes clusters across multiple regions and clouds
Build and maintain infrastructure for the platform that powers LLM inference workloads globally
Own networking, including VPCs, peering, load balancing, DNS, service mesh, CNI
Manage GPU infrastructure and autoscaling for ML workloads
Write and maintain infrastructure as code (Pulumi / Python)
Operate and improve observability: monitoring, alerting, tracing, logging
Deep experience with Kubernetes in production at scale: networking, storage, scheduling, upgrades
Strong background in AWS
Hands-on experience with infrastructure as code (Pulumi, Terraform, or similar)
Solid understanding of Linux networking
Track record with high-traffic production ML systems
Programming fluency, Python preferred
Experience with large-scale LLM / ML inference infrastructure (GPU scheduling, model serving, vLLM, Kube Ray, Kubernetes-native tooling)
Kubernetes networking depth with Cilium or other CNI plugins; service mesh (Istio, Envoy)
Multi-cloud infrastructure
Background in site reliability engineering including SLOs, incident response, capacity planning
We're a small, flat, close-knit team working to make intelligence dependable enough to become part of everyday software. We work fully in person from our San Francisco office near Embarcadero station. We love what we do and care deeply about the work.
We strive for excellence and craftsmanship and won't stop until we get there. When the team wins, we all win, and we enjoy collaborating and inspiring each other to grow—as a team and as individuals.
We value emotional honesty, kindness, and bringing your whole self to work. We build machines; we don't try to be machines.
We want Type Safe to be the place where you do the most impactful work of your career and help define our future as a company.
We provide100% covered health insurance
Daily lunch and dinner
Visa sponsor ships
401K plans
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).