Core Qualifications

• 5+ years of shipping production systems in a systems language. Rust is the house language, but polyglots are welcome — deep Go, C/C++, or Zig with genuine appetite for Rust counts. Async runtimes, memory-safety discipline, and debugging at the syscall boundary should be familiar territory.
• Operated Kubernetes workloads that other people depended on — controllers or operators, scheduling, autoscaling, node lifecycle. You've been paged, and the experience changed how you build.
• Strong ability to threat-model isolation boundaries (namespaces, cgroups, seccomp, hypervisors), including identifying what an untrusted guest could observe, forge, or exhaust, and applying security best practices for agentic execution — least privilege, no credentials in the sandbox, audit trails, and human approval on write actions.
• Hands-on experience deploying or operating open-weight LLM serving infrastructure (vLLM/SGLang or similar), including packaging models into reliable, metered production endpoints.
• Performance discipline in distributed systems: you measure before you optimize, and you can tell the story of a latency you killed with the numbers attached.
• Practical depth in some of our core stack — Rust (tokio), Python/FastAPI, Kubernetes operators (controller-runtime/Kubebuilder/CRDs), KEDA, Karpenter, GPU device plugins/DRA — with a genuine willingness to research your way into the rest.
• Familiarity with isolation technology (Firecracker, Kata, gVisor, or comparable), secrets management and egress control (Vault/KMS-class), and hosting stateful systems (vector stores like pgvector/Qdrant, graph stores like Neo4j) with backup and failover discipline.
• Comfort operating across cloud and GPU substrates — AWS/Azure/GCP plus managed GPU clouds — using infrastructure-as-code (Terraform/OpenTofu, Bicep) and observability tooling (OpenTelemetry).
• Bachelor's Degree; Master's is a plus

Why AZX!

• Be part of a fast-growing, profitable, mission-driven company with industry-leading clients tackling the massive opportunity of AI transformation in critical industries.
• Competitive early-stage startup compensation (based on capabilities, experience, and location)
• Bonus eligibility
• Health insurance with meaningful coverage for dependents
• Flexible paid time off
• Equity
• Fully remote culture with a cluster of teammates in Seattle

Core Qualifications

• 5+ years of shipping production systems in a systems language. Rust is the house language, but polyglots are welcome — deep Go, C/C++, or Zig with genuine appetite for Rust counts. Async runtimes, memory-safety discipline, and debugging at the syscall boundary should be familiar territory.
• Operated Kubernetes workloads that other people depended on — controllers or operators, scheduling, autoscaling, node lifecycle. You've been paged, and the experience changed how you build.
• Strong ability to threat-model isolation boundaries (namespaces, cgroups, seccomp, hypervisors), including identifying what an untrusted guest could observe, forge, or exhaust, and applying security best practices for agentic execution — least privilege, no credentials in the sandbox, audit trails, and human approval on write actions.
• Hands-on experience deploying or operating open-weight LLM serving infrastructure (vLLM/SGLang or similar), including packaging models into reliable, metered production endpoints.
• Performance discipline in distributed systems: you measure before you optimize, and you can tell the story of a latency you killed with the numbers attached.
• Practical depth in some of our core stack — Rust (tokio), Python/FastAPI, Kubernetes operators (controller-runtime/Kubebuilder/CRDs), KEDA, Karpenter, GPU device plugins/DRA — with a genuine willingness to research your way into the rest.
• Familiarity with isolation technology (Firecracker, Kata, gVisor, or comparable), secrets management and egress control (Vault/KMS-class), and hosting stateful systems (vector stores like pgvector/Qdrant, graph stores like Neo4j) with backup and failover discipline.
• Comfort operating across cloud and GPU substrates — AWS/Azure/GCP plus managed GPU clouds — using infrastructure-as-code (Terraform/OpenTofu, Bicep) and observability tooling (OpenTelemetry).
• Bachelor's Degree; Master's is a plus

Why AZX!

• Be part of a fast-growing, profitable, mission-driven company with industry-leading clients tackling the massive opportunity of AI transformation in critical industries.
• Competitive early-stage startup compensation (based on capabilities, experience, and location)
• Bonus eligibility
• Health insurance with meaningful coverage for dependents
• Flexible paid time off
• Equity
• Fully remote culture with a cluster of teammates in Seattle

Core Qualifications

• 5+ years of shipping production systems in a systems language. Rust is the house language, but polyglots are welcome — deep Go, C/C++, or Zig with genuine appetite for Rust counts. Async runtimes, memory-safety discipline, and debugging at the syscall boundary should be familiar territory.
• Operated Kubernetes workloads that other people depended on — controllers or operators, scheduling, autoscaling, node lifecycle. You've been paged, and the experience changed how you build.
• Strong ability to threat-model isolation boundaries (namespaces, cgroups, seccomp, hypervisors), including identifying what an untrusted guest could observe, forge, or exhaust, and applying security best practices for agentic execution — least privilege, no credentials in the sandbox, audit trails, and human approval on write actions.
• Hands-on experience deploying or operating open-weight LLM serving infrastructure (vLLM/SGLang or similar), including packaging models into reliable, metered production endpoints.
• Performance discipline in distributed systems: you measure before you optimize, and you can tell the story of a latency you killed with the numbers attached.
• Practical depth in some of our core stack — Rust (tokio), Python/FastAPI, Kubernetes operators (controller-runtime/Kubebuilder/CRDs), KEDA, Karpenter, GPU device plugins/DRA — with a genuine willingness to research your way into the rest.
• Familiarity with isolation technology (Firecracker, Kata, gVisor, or comparable), secrets management and egress control (Vault/KMS-class), and hosting stateful systems (vector stores like pgvector/Qdrant, graph stores like Neo4j) with backup and failover discipline.
• Comfort operating across cloud and GPU substrates — AWS/Azure/GCP plus managed GPU clouds — using infrastructure-as-code (Terraform/OpenTofu, Bicep) and observability tooling (OpenTelemetry).
• Bachelor's Degree; Master's is a plus

Why AZX!

• Be part of a fast-growing, profitable, mission-driven company with industry-leading clients tackling the massive opportunity of AI transformation in critical industries.
• Competitive early-stage startup compensation (based on capabilities, experience, and location)
• Bonus eligibility
• Health insurance with meaningful coverage for dependents
• Flexible paid time off
• Equity
• Fully remote culture with a cluster of teammates in Seattle

Core Qualifications

• 5+ years of shipping production systems in a systems language. Rust is the house language, but polyglots are welcome — deep Go, C/C++, or Zig with genuine appetite for Rust counts. Async runtimes, memory-safety discipline, and debugging at the syscall boundary should be familiar territory.
• Operated Kubernetes workloads that other people depended on — controllers or operators, scheduling, autoscaling, node lifecycle. You've been paged, and the experience changed how you build.
• Strong ability to threat-model isolation boundaries (namespaces, cgroups, seccomp, hypervisors), including identifying what an untrusted guest could observe, forge, or exhaust, and applying security best practices for agentic execution — least privilege, no credentials in the sandbox, audit trails, and human approval on write actions.
• Hands-on experience deploying or operating open-weight LLM serving infrastructure (vLLM/SGLang or similar), including packaging models into reliable, metered production endpoints.
• Performance discipline in distributed systems: you measure before you optimize, and you can tell the story of a latency you killed with the numbers attached.
• Practical depth in some of our core stack — Rust (tokio), Python/FastAPI, Kubernetes operators (controller-runtime/Kubebuilder/CRDs), KEDA, Karpenter, GPU device plugins/DRA — with a genuine willingness to research your way into the rest.
• Familiarity with isolation technology (Firecracker, Kata, gVisor, or comparable), secrets management and egress control (Vault/KMS-class), and hosting stateful systems (vector stores like pgvector/Qdrant, graph stores like Neo4j) with backup and failover discipline.
• Comfort operating across cloud and GPU substrates — AWS/Azure/GCP plus managed GPU clouds — using infrastructure-as-code (Terraform/OpenTofu, Bicep) and observability tooling (OpenTelemetry).
• Bachelor's Degree; Master's is a plus

Why AZX!

• Be part of a fast-growing, profitable, mission-driven company with industry-leading clients tackling the massive opportunity of AI transformation in critical industries.
• Competitive early-stage startup compensation (based on capabilities, experience, and location)
• Bonus eligibility
• Health insurance with meaningful coverage for dependents
• Flexible paid time off
• Equity
• Fully remote culture with a cluster of teammates in Seattle