DevOps Engineer

About the role

We are seeking experienced DevOps, Site Reliability, and Cloud Infrastructure Engineers to contribute to projects focused on evaluating and improving next-generation AI coding systems. In this role, you will work with advanced AI coding agents on realistic infrastructure engineering tasks and assess the quality, reliability, and correctness of their outputs.

Responsibilities

• Use advanced AI coding agents to complete and evaluate complex DevOps, SRE, and infrastructure engineering tasks.
• Review AI-generated implementations involving cloud platforms, Kubernetes, CI/CD pipelines, infrastructure automation, and observability.
• Identify bugs, edge cases, security concerns, reliability issues, and potential failure modes in AI-generated solutions.
• Compare outputs from multiple AI coding models and assess their relative strengths, weaknesses, and technical accuracy.
• Evaluate infrastructure solutions against real-world production engineering standards and best practices.
• Apply professional judgment to realistic cloud infrastructure, deployment, monitoring, and reliability scenarios.
• Provide structured technical feedback to help improve AI coding model performance.
• Document findings clearly and consistently according to project evaluation criteria.

Qualifications

• 2+ years of professional experience in DevOps, Site Reliability Engineering (SRE), Cloud Engineering, Infrastructure Engineering, or a related field.
• Hands-on experience with one or more major cloud platforms, including AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Strong experience with Kubernetes, Terraform, CI/CD pipelines, infrastructure as code, and/or observability platforms.
• Experience working with production-scale infrastructure and distributed systems.
• Regular experience using AI coding tools such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar platforms.
• Ability to critically evaluate AI-generated code and infrastructure configurations.
• Strong understanding of system reliability, deployment automation, monitoring, scalability, and troubleshooting.
• Excellent analytical and problem-solving skills with strong attention to technical detail.