TypeSafe AI is an AI lab building machine-native intelligence infrastructure for automation, designed to make decisions within software by combining the intelligence of LLMs with the efficiency and reliability of code into a new shape of AI: System One Models. Based in San Francisco, TypeSafe AI recently launched its first public model, Jev.
While others chase benchmarks and academic puzzles, we’ve been quietly rethinking the LLM stack from first principles — building a new kind of general frontier model designed for real-world reliability, decision-making, and autonomy in production.
We’re a small, fast-moving team from OpenAI, Google Brain, and Meta/FAIR, backed by top-tier investors. Since mid-2024, we’ve been engineering the foundation for what comes after the current “state-of-the-art” — a model that actually gets things done.
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.
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
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
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 TypeSafe to be the place where you do the most impactful work of your career and help define our future as a company.
Base salary of $150k–250k plus equity, based on leveling
100% covered health insurance
Daily lunch and dinner
Visa sponsorships
401K plans
Job details are sourced from the employer's original posting.
Open job postingAbout the company
TypeSafe AI is building a platform to help developers build and deploy AI applications more reliably and efficiently. They focus on composable AI and developer experience.