DevOps / SRE Test Bench Engineer

We are looking for a technically strong engineer to design and validate realistic infrastructure troubleshooting challenges for AI systems. In this fully remote, hourly contract role, you will build intentionally broken Linux and containerized environments that simulate complex, production-like incidents. You will investigate failures across interconnected services, identify root causes, and develop reliable recovery solutions. Your work will also include creating automated verification scripts to confirm that issues are genuinely resolved. This opportunity is ideal for an engineer who enjoys deep technical debugging, infrastructure automation, and solving ambiguous problems without relying on predefined runbooks. You will contribute to challenging, reproducible test scenarios that help evaluate practical engineering capabilities.

• At least 2 years of hands-on experience in DevOps, Site Reliability Engineering (SRE), platform engineering, infrastructure engineering, or a related technical field.

• Strong Linux administration and command-line skills, including SSH, shell scripting, process management, log analysis, file permissions, networking, and system services.

• Strong practical expertise in Docker and Kubernetes, including diagnosing container failures, broken deployments, service connectivity issues, and orchestration problems.

• Experience with databases and infrastructure components such as PostgreSQL, Redis, message queues, storage systems, replication, and recovery mechanisms.

• Proven ability to troubleshoot production-like environments involving multiple interdependent services.

• Familiarity with CI/CD pipelines, Infrastructure as Code (IaC), and cloud infrastructure.

• Strong analytical and investigative skills, with the ability to work independently through ambiguous failures, identify underlying causes, and implement effective solutions without depending on predefined procedures.

• A testing-oriented mindset and experience creating automated checks, validation scripts, and deterministic verification mechanisms.

• Proficiency in Python or Bash for environment setup, troubleshooting automation, and test development.

Good-to-have skills:

• Experience with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.

• Familiarity with Nginx, systemd, Logical Volume Manager (LVM), and Linux security hardening.

• Understanding of distributed systems, service dependencies, and fault-recovery mechanisms.

• Experience using AI coding agents or AI-assisted software engineering tools.