About the Role
About AZX
Our mission is to accelerate positive impact in critical industries through AI transformation. We specialize in physics-informed ML and enterprise AI solutions that directly address climate and sustainability challenges.
We're growing quickly and already work with category-leaders in real estate (CBRE), energy (LevelTen Energy), logistics (Flexe) and utilities.
We bootstrapped profitably for our first year and are now backed by leading investors focused on AI, climate and energy.
We work on challenges in clean energy, decarbonization, climate risk, energy systems, and global economics. We're building our company for long-term success and aim to create the ultimate place to work for those passionate about AI and making a positive impact.
About This Role
You will be responsible for owning the layer where AI work physically happens: the machines, the isolation boundary, and the models running on them. This role anchors on two systems. The first is our inference control plane: open-weight models and custom task-model zoos, hosted and operated across managed GPU clouds and customer-managed Kubernetes clusters, with scale-to-zero economics, cold-start discipline, and per-token cost accounting that stays correct even when a client disconnects mid-stream, along with the Kubernetes layer those workloads live on (operators, autoscaling, node lifecycle). The second is our agent-sandboxing platform: hardware-isolated microVMs for running untrusted, agent-generated code securely and compliantly by construction, where agents operate with least privilege, never see a credential, and a human gates anything that writes to a system of record. You'll write Rust in the morning, a Kubernetes controller after lunch, and a FastAPI control-plane endpoint before you go home, building the fork engine, the guest agent, and the multi-substrate model lifecycle.
Responsibilities
- Manage the serving tier for open-weight models: engine deployment and configuration, cold-start strategy, per-model SLOs, and upgrade/canary discipline.
- Administer the Kubernetes layer for inference and sandbox workloads: operators and CRDs, autoscaling (KEDA/Karpenter-class), GPU scheduling and sharing, and node lifecycle.
- Own the stateful data plane end to end with restore procedures that are regularly tested.
- Oversee the sandbox runtime and its host-side control plane: lifecycle, exec, snapshot/fork, teardown, metering, and the threat model of the isolation boundary.
- Direct the FastAPI control-plane services, Terraform/OpenTofu, Bicep, and the dashboards.
- Run the layer the backend services team builds on, expect to debug into their services, and expect them to read your dashboards.
- Manage the open-source posture: build to OSS standards and release as it matures, with reviewed PRs, real docs, and reproducible builds.
Additional Information
Must be able to travel 2x/year for company summits.
Applicants must be currently authorized to work in the United States on a full-time basis.
We are unable to sponsor or take over sponsorship of employment visas at this time.
Please note that our interview process includes a written take-home assignment followed by a live two-hour technical session with our engineering team, so if that format isn't a good fit, we'd ask that you not apply.
Please only apply to a maximum of 2 roles at a time; any applicants who apply to more than 2 roles within a 6 month period will automatically be disqualified.
Next Steps
If this job sounds like a great fit but you don't check ALL of these qualification boxes, we'd still love to hear from you!
Required 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.
Requirements
Rust programming
5+ years of experience in Rust or similar systems languages.
Kubernetes management
Experience administering Kubernetes clusters for inference and sandbox workloads.
AI infrastructure
Knowledge of managing AI inference control planes and deployment strategies.
Microservices architecture
Familiarity with building and managing microservices and control-plane services.
Nice to Have
Familiarity with building control-plane endpoints using FastAPI.
Experience in contributing to open-source projects and maintaining OSS standards.
Benefits
Remote work
Flexible remote work options available.
Travel opportunities
Opportunity to travel for company summits twice a year.