About the Role
We are seeking an experienced DevOps Engineer to contribute technical expertise to large language model (LLM) training and evaluation workflows. The role involves reviewing infrastructure scenarios, assessing AI-generated technical responses, and developing practical DevOps tasks to help improve AI performance across cloud infrastructure, automation, deployment, and troubleshooting.
You'll apply your hands-on knowledge of cloud platforms and DevOps practices to evaluate technical accuracy, reliability, security, and scalability. This opportunity is suited to professionals with experience in DevOps, cloud engineering, or site reliability engineering who are interested in AI-assisted development and technical model evaluation.
Key Responsibilities
•Review DevOps tasks, infrastructure scenarios, and AI-generated technical responses as part of LLM training and evaluation workflows.
•Assess model outputs for technical accuracy, reliability, security, scalability, and alignment with DevOps best practices.
•Create and review DevOps prompts, infrastructure scenarios, coding tasks, and reference solutions.
•Develop evaluation criteria to assess the quality and correctness of AI-generated technical content.
•Provide expert feedback to improve LLM performance in cloud infrastructure, automation, deployment, and troubleshooting workflows.
•Apply practical DevOps knowledge to identify technical errors, potential security issues, and gaps in AI-generated solutions.
Required Qualifications
•3–8 years of professional experience in DevOps, cloud engineering, site reliability engineering (SRE), or a related technical role.
•Hands-on experience with one or more major cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform (GCP).
•Strong knowledge of Docker, Kubernetes, CI/CD pipelines, and Infrastructure as Code (IaC).
•Familiarity with Linux administration, networking, Git, scripting, monitoring, and cloud automation.
•Strong troubleshooting skills and an understanding of reliable, secure, and scalable infrastructure practices.
•Ability to review technical solutions critically and assess whether they follow established DevOps standards.
•Experience with or a strong interest in LLM training, AI-assisted development, code evaluation, prompt engineering, or AI-enabled DevOps workflows.
Compensation and Work Arrangement
•Contractor position with hourly compensation ranging from $30 to $60.
•Remote work arrangement.
•Flexible engagement details have not been specified.
This role offers DevOps professionals an opportunity to apply their infrastructure and automation expertise to the evaluation and improvement of AI-generated technical solutions.