Kubernetes & Distributed Systems Benchmark Engineer

remote work; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Status is building the Logos ecosystem for a freer internet. This role focuses on designing and executing large-scale evaluations of distributed systems, including performance and reliability testing for Logos (λ) and related projects.

The ideal candidate will design, configure, and optimize Kubernetes clusters for large-scale experiments, improve scalability, and set up observability stacks. You will automate infrastructure and collaborate with researchers to ensure reproducible benchmarks.

Qualifications

• Extensive experience with Kubernetes and container orchestration.
• Solid understanding of cloud infrastructure, Linux, and networking.
• Familiarity with Grafana, Prometheus and VictoriaMetrics for observability.
• Infrastructure as code with Terraform, Ansible, Helm.
• Proficient in Python scripting; interest in distributed systems.

Responsibilities

• Design, configure, and optimize Kubernetes clusters for large-scale experiments.
• Improve cluster scalability and resource utilization for complex deployments.
• Set up and optimize monitoring, logging, and observability stacks.
• Collaborate with researchers and engineers to streamline workflows.
• Automate infrastructure and deployment to increase reliability.
• Troubleshoot and profile distributed workloads for benchmarking.

Skills

Kubernetes & container orchestration

Cloud infrastructure understanding

Linux systems & networking

Observability & monitoring

Python scripting

Distributed systems / P2P / blockchain

Tools

Grafana

Prometheus

VictoriaMetrics

Terraform

Ansible

Helm

Job description

Status is building the Logos ecosystem for a freer internet. This role focuses on designing and executing large-scale evaluations of distributed systems, including performance and reliability testing for Logos (λ) and related projects.

The ideal candidate will design, configure, and optimize Kubernetes clusters for large-scale experiments, improve scalability, and set up observability stacks. You will automate infrastructure and collaborate with researchers to ensure reproducible benchmarks.