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# Infrastructure Engineer - Developer Platform

- **Company:** Typesafe AI Inc.
- **Location:** San Francisco, CA, United States
- **Salary:** $180,000.0 - $280,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Computer Programming, Computer Networks, Domain Name System (DNS), Python (Programming Language), Peering, Reliability Engineering, Data Logging, Pulumi, Load Balancing, Istio, Large Language Models, Multi-Cloud, Kubernetes, Machine Learning Operations, Hardware Infrastructure, Terraform, Programming Languages
- **Published:** June 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1fbb9df241d465d0

## About the Role

Do you have experience in Programming languages?, * 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, 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

## Description

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., * 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


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