AI Chaos Engineering Simulation Developer

Ulvex Systems

Remote · $160k – $200k / year · Full-time · Posted 3 months ago

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About the role

We just closed our Series B and are scaling our observability platform fast. We need a senior engineer who can build the chaos simulation layer our largest customers keep asking for. Today, teams find out their alerting and root-cause pipelines have blind spots only after a real incident. You will build a controlled fault-injection framework that simulates realistic production failures against our own platform and customer sandbox environments, then validates whether our detection pipeline catches them. You'll work closely with the SRE anomaly detection team, using their existing pipelines as both the target of your chaos experiments and the validation harness for whether the experiments are actually useful.

Fully remote.

Responsibilities

Build a fault-injection framework simulating realistic Kubernetes and service-level failures
Drive adoption of chaos experiments as a standard pre-release validation step
Integrate simulation runs into existing Airflow-orchestrated pipelines
Partner with the anomaly detection team to close detection blind spots surfaced by experiments
Own the reporting layer that summarizes chaos experiment coverage over time

Requirements

6+ years in infrastructure or reliability engineering roles
Deep hands-on experience with Kubernetes and Docker in production
Comfortable orchestrating workflows with Airflow
Experience designing controlled failure injection or similar reliability testing