Member of Technical Staff | Observability & Reliability

Avra is a frontier AI lab building relational foundation models. In this role, the Member of Technical Staff will join the Platform team as the go-to expert on observability and reliability. Customers make real-time decisions based on Avra's responses, and Avra's cloud is one more dataplane alongside the dataplanes operated inside customer environments, so observability and reliability must work the same way everywhere. Success is measured by 99.9% serving availability with incidents trending down, MTTR including on-premise incidents, near-zero drift between desired and actual state, and all agents active and reporting across every dataplane.

Responsibilities

Evolve the observability stack for logs, metrics, traces, and alerting; Make sure every dataplane, in the cloud and on-premise, reports its active release, health, heartbeat, logs, metrics, and usage to the control plane; Bring telemetry into customer clusters within a model where agents only make outbound connections; Detect drift between the desired state and what's actually running in each environment; Monitor the health of deployment and runtime agents; Provide visibility into ephemeral workloads, such as the Ray clusters that run batch inference; Define SLOs, lead incident response and postmortems, and reduce MTTR, including when a fix requires coordinating with the customer; Reduce telemetry cost by cutting redundant data and increasing useful signal

Requirements

Deep experience with OpenTelemetry and observability backends; Hands-on practice with SLOs, error budgets, actionable alerting, and incident management; Strong experience with Kubernetes and infrastructure as code (Terraform / Helm); Experience operating software in environments you don't fully control; Production-quality code and reviews, and a willingness to operate what you build

Nice to have

Shipping software to customer-hosted Kubernetes (e.g., Helm, outbound-only connectivity); GCP or GKE, AWS or EKS; ML multi-node/multi-cluster workloads in production; Financial services or regulated environments