Are you an experienced DevOps Engineer, Site Reliability Engineer (SRE), or Cloud Engineer who regularly uses AI coding tools like Cursor, Claude Code, Codex, or Windsurf? Mercor is currently recruiting infrastructure professionals for an exciting AI research project with a leading frontier AI laboratory.
This fully remote contract role allows qualified engineers to earn approximately $400 per accepted task, with most tasks taking only 2 to 3 hours after onboarding and ramp-up.
About the Opportunity
Mercor is partnering with a world-leading AI research organization on a Frontier Code Agents project designed to improve the capabilities of advanced AI coding models.
As a contributor, you’ll evaluate AI-generated infrastructure solutions, identify reliability issues, and help improve how AI systems handle real-world DevOps, cloud, and SRE workflows.
Due to high demand, available positions are limited and filled on a first-come, first-served basis.
Job Details
- Position: DevOps / SRE / Cloud Engineer
- Company: Mercor
- Work Type: Independent Contractor
- Location: Fully Remote
- Compensation: $400 per accepted task
- Estimated Task Duration: 2–3 hours
- Project Type: Frontier AI Coding Model Evaluation
- Payment Method: Weekly via Stripe or Wise
Eligible Countries
Candidates can apply from a wide range of countries across North America and Europe, including:
- United States
- Canada
- United Kingdom
- Germany
- France
- Netherlands
- Switzerland
- Sweden
- Spain
- Italy
- Portugal
- Poland
- Austria
- Belgium
- Ireland
- Norway
- Australia
And many other eligible countries listed by Mercor.
What You’ll Do
Evaluate AI Coding Agents
Use advanced AI coding assistants to solve and review realistic infrastructure engineering tasks.
Review Infrastructure Solutions
Analyze AI-generated implementations involving:
- Cloud platforms
- Kubernetes clusters
- Infrastructure automation
- CI/CD pipelines
- Monitoring systems
- Reliability engineering workflows
Identify Problems and Risks
Detect:
- Bugs
- Reliability issues
- Configuration mistakes
- Edge cases
- Security concerns
- Operational risks
Compare Multiple AI Models
Assess the strengths and weaknesses of outputs generated by different frontier AI coding systems.
Apply Engineering Expertise
Use professional judgment to evaluate whether AI-generated solutions are production-ready and technically sound.
Required Qualifications
Applicants should have:
Professional Experience
- Minimum 2 years of experience in:
- DevOps Engineering
- Site Reliability Engineering (SRE)
- Cloud Engineering
Cloud & Infrastructure Skills
Experience with one or more of:
- Amazon Web Services (AWS)
- Microsoft Azure
- Google Cloud Platform (GCP)
- Kubernetes
- Terraform
- Docker
- Infrastructure as Code (IaC)
CI/CD Knowledge
Hands-on experience building and managing:
- Continuous Integration pipelines
- Continuous Delivery workflows
- Deployment automation systems
AI Coding Tools Experience
Regular usage of AI coding agents such as:
- Cursor
- Claude Code
- Codex
- Windsurf
- Gemini CLI
- Similar AI-assisted development tools
Preferred Qualifications
Candidates with the following experience may have an advantage:
Production Infrastructure Experience
Experience managing production-scale systems with high availability and reliability requirements.
Observability and Monitoring
Knowledge of:
- Prometheus
- Grafana
- Datadog
- New Relic
- OpenTelemetry
- Logging and monitoring platforms
Infrastructure Security
Understanding of infrastructure hardening, cloud security, and operational best practices.
Compensation and Earnings Potential
Mercor pays:
- $400 per accepted task
- Typical completion time: 2–3 hours
- Weekly payments through Stripe or Wise
For experienced contributors, this can translate into highly competitive hourly earnings depending on efficiency and task acceptance rates.
Project Timeline
Unlike traditional part-time jobs, this project operates in sprint-based cycles:
- Tasks become available based on client demand
- Work may occur in 12–24 hour project windows
- Contributors choose whether to participate in available sprints
- Additional opportunities may become available based on performance
Why This Role Stands Out
Flexible Remote Work
Work entirely online from your preferred location.
Cutting-Edge AI Exposure
Gain hands-on experience evaluating some of the world’s most advanced AI coding systems.
High Compensation
Earn premium rates for applying real-world infrastructure engineering expertise.
Technical Challenge
Work on realistic cloud, Kubernetes, automation, and reliability scenarios rather than repetitive data-labeling tasks.
Future Opportunities
Strong performers may be invited to additional Mercor projects involving AI model evaluation and engineering research.
Contract Information
Important details include:
- Independent contractor engagement
- Fully remote work environment
- Flexible schedule
- Project duration may vary based on client requirements
- Weekly payments for accepted work
- No access to confidential information from employers or clients
- H1-B and STEM OPT candidates are currently not eligible
Final Thoughts
The DevOps / SRE / Cloud Engineer opportunity at Mercor is ideal for infrastructure professionals who enjoy solving complex cloud and reliability challenges while exploring the future of AI-assisted software engineering. With flexible scheduling, remote work, and earnings of approximately $400 per accepted task, this role offers an attractive way to monetize your expertise while contributing to next-generation AI systems.
If you have experience with AWS, Azure, Kubernetes, Terraform, CI/CD pipelines, and AI coding tools, this opportunity is worth considering.