Developer Infrastructure Engineer (AI Workflow Evaluation)
Summary
This role involves testing and evaluating AI-assisted developer and infrastructure workflows for technical accuracy and usability. Candidates will use their background in DevOps, SRE, or cloud engineering to review AI outputs across tools like AWS, Kubernetes, and Terraform.
About Us
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
Role Overview
We are looking for experienced professionals from software engineering, DevOps, SRE, cloud, platform, or infrastructure engineering backgrounds to test and evaluate AI-assisted workflows across modern developer and workplace tools. The role focuses on assessing technical accuracy, workflow realism, command and configuration quality, platform interactions, and practical usability. No prior AI evaluation experience is required, but hands-on use of AI coding or productivity agents is highly relevant.
CONTRACT: Contractor assignment
LOCATIONS: Remote, GLOBAL
HOURLY RATE: $30 - $80/h
NOTES: Strong hands-on experience with developer, cloud, and infrastructure tooling is required.
Responsibilities
- Test and validate AI-assisted developer and infrastructure workflows.
- Evaluate commands, configurations, and outputs across cloud and platform engineering scenarios.
- Review workflows involving GitHub, GitLab, JIRA, AWS, Azure, GCP, Kubernetes, Docker, and Terraform.
- Identify technical inaccuracies, broken steps, unrealistic assumptions, or workflow gaps.
- Assess how AI agents interact with connected workplace tools such as Slack, Google Drive, and Microsoft 365.
- Document observations and provide clear, actionable technical feedback.
- Recommend workflow improvements based on real-world engineering standards.
- Participate in asynchronous review and virtual discussions to clarify task requirements.
- Evaluate whether AI-generated solutions are practical, reproducible, and technically sound.
- Maintain clear documentation across all submitted evaluations.
Requirements
- Professional experience in software engineering, DevOps, SRE, cloud, platform, or infrastructure engineering.
- Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.
- Practical experience with Kubernetes, Docker, Terraform, or comparable infrastructure tooling.
- Familiarity with developer platforms such as GitHub, GitLab, or JIRA.
- Experience with CI/CD pipelines and modern infrastructure or platform workflows.
- Professional experience using AI agents such as ChatGPT, Claude Code, Claude Cowork, Codex, or similar tools.
- Ability to evaluate technical workflows and identify incorrect or inefficient implementations.
- Strong written and spoken English.
As published by workable
First name, Last name, Email, Phone, Address, Education, Experience, Summary, Resume
- Please provide a valid and up-to-date LinkedIn profile URL that clearly reflects your professional experience, technical skills, and employment history relevant to the job. Example format: https://www.linkedin.com/in/yourprofile Applications with incomplete, inactive, or non-professional LinkedIn profiles may not be considered.
- Briefly describe your professional experience and the types of workflows you personally handle in your work. written answer
- Which professional platforms or products do you use regularly in your work? Briefly describe what you use them for. written answer
- Approximately how many hours per week do you actively use AI assistants such as Claude/Cowork, and Codex for professional work? choose any
- Describe the most advanced AI workflow you regularly use in your professional work. What task does it perform, which AI platform(s) and business tools does it use, and what makes the workflow complex? written answer
- Which AI platforms and workplace connectors or integrations have you used professionally (e.g., Google Drive, Gmail, Slack, Notion, Jira, Confluence, GitHub, Microsoft 365, SharePoint, Salesforce)? Describe one workflow where you use AI with two or more connected applications at the same time, including what information the AI retrieves and what actions or outputs it produces. written answer
- How soon can you start the work? (in days)
- How many hours per week are you available to work?
- What is your expected hourly rate in USD?