Infrastructure Engineer (Kubernetes Specialist)
Join TypeSafe AI as an Infrastructure Engineer to build and operate scalable infrastructure for AI products.
Posted by employer 7 months ago
First seen on Joblaze 1 hour ago
Last verified on the company career page 1 hour ago
What you'll build
- Design, deploy, and operate Kubernetes clusters
- Build and maintain infrastructure for LLM inference workloads
- Own networking including VPCs and load balancing
- Manage GPU infrastructure for ML workloads
- Operate and improve observability
Must have
- Deep experience with Kubernetes in production at scale
- Strong background in AWS
- Hands-on experience with infrastructure as code
- Solid understanding of Linux networking
- Track record with high-traffic production ML systems
- Programming fluency, Python preferred
Nice to have
- Experience with large-scale LLM / ML inference infrastructure
- Kubernetes networking depth with Cilium
- Multi-cloud infrastructure
- Background in site reliability engineering
Requirements
- Visa
- Sponsorship available
Not disclosed in this posting: compensation, years of experience.
Benefits
Joblaze summary
The Infrastructure Engineer at TypeSafe AI is responsible for designing and managing the infrastructure that supports their AI products, focusing on Kubernetes clusters and networking for efficient model inference. Key skills include deep Kubernetes experience, AWS proficiency, and familiarity with infrastructure as code tools like Pulumi or Terraform. This role is ideal for someone with a strong background in high-traffic production ML systems and a collaborative mindset, fitting well within a small, dedicated team committed to building reliable AI solutions.
Joblaze insights
- Listed today — first seen on Joblaze October 19, 2026. Last confirmed on TypeSafe AI's careers page October 19, 2026.
- Kubernetes appears in 59.3% of 118 comparable mid devops/sre roles in United States; Pulumi appears in 0.8% of 118 comparable mid devops/sre roles in United States.
Quick facts
- Is the Infrastructure Engineer (Kubernetes Specialist) role remote?
- No — this is an on-site role in San Francisco, United States.
- Where is the role based?
- TypeSafe AI is hiring for this position in San Francisco, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AWS, Kubernetes, Linux, Pulumi, Python, Terraform.
- Does TypeSafe AI sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- TypeSafe AI targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Infrastructure Engineer (Kubernetes Specialist) role at TypeSafe AI.
From the original posting
About the role
We're looking for an Infrastructure Engineer to build and operate the infrastructure behind TypeSafe 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 do
Design, 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
Requirements
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
Nice to have
Experience with large-scale LLM / ML inference infrastructure (GPU scheduling, model serving, vLLM, KubeRay, 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 provide
100% covered health insurance
Daily lunch and dinner
Visa sponsorships
401K plans
Standard company text repeated across TypeSafe AI's postings is omitted here.