Senior Software Engineer (AI Inference & Runtime Platform)

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. We're looking for individuals who've built this class of stack (an inference-serving or serverless-GPU platform), operated it hard at scale, or ideally both.

- 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.