AI Summary
We're looking for experienced software engineers to evaluate and improve AI systems that generate real-world infrastructure solutions. Your hands-on expertise will directly shape how AI understands cloud architecture, DevOps workflows, and production systems. Work on cutting-edge AI projects with top research labs and influence how large language models understand infrastructure.
Key Highlights
Review AI-generated solutions for cloud architecture, DevOps workflows, and IT infrastructure
Evaluate code, configurations, and system designs for correctness, security, and best practices
Provide structured, actionable feedback to improve AI accuracy in software engineering and IT domains
Key Responsibilities
Review AI-generated solutions for cloud architecture, DevOps workflows, and IT infrastructure
Evaluate code, configurations, and system designs for correctness, security, and best practices
Provide structured, actionable feedback to improve AI accuracy in software engineering and IT domains
Test and validate solutions across AWS, GCP, Azure, and on-premises environments
Assess troubleshooting recommendations for production systems and incident response scenarios
Technical Skills Required
Benefits & Perks
Fully remote
Flexible contract role
Autonomy
Meaningful impact
Ongoing opportunity
Nice to Have
Experience with monitoring and observability tools
Knowledge of networking, security, or compliance frameworks
Background in system design or architecture reviews
Scripting proficiency in Python, Bash, or similar languages
Job Description
Software & IT Infrastructure Expert (AI Training)
About The Role
AI is only as good as the experts behind it. We're looking for experienced software engineers, DevOps engineers, systems administrators, and IT architects to evaluate and improve AI systems that generate real-world infrastructure solutions. Your hands-on expertise will directly shape how AI understands cloud architecture, DevOps workflows, and production systems.
This is a fully remote, flexible contract role — work on your own schedule, on your own terms.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
- Review AI-generated solutions for cloud architecture, DevOps workflows, and IT infrastructure
- Evaluate code, configurations, and system designs for correctness, security, and best practices
- Identify errors, misconfigurations, and gaps in AI-generated infrastructure guidance
- Test and validate solutions across AWS, GCP, Azure, and on-premises environments
- Provide structured, actionable feedback to improve AI accuracy in software engineering and IT domains
- Assess troubleshooting recommendations for production systems and incident response scenarios
- Work independently and asynchronously — no meetings, no fixed hours
Interested in remote work opportunities in IT & Network Engineering? Discover IT & Network Engineering Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- 3+ years of professional experience as a software engineer, systems administrator, DevOps engineer, or IT architect
- Hands-on experience with production systems and real-world infrastructure troubleshooting
- Working knowledge of at least one major cloud platform (AWS, GCP, and/or Azure)
- Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), or infrastructure-as-code tools
- Strong analytical thinking and sharp attention to technical detail
- Clear written communication — you can explain complex concepts concisely
- No prior AI or machine learning experience required
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Experience with monitoring and observability tools (Datadog, Prometheus, CloudWatch)
- Knowledge of networking, security, or compliance frameworks
- Background in system design or architecture reviews
- Scripting proficiency in Python, Bash, or similar languages
- Work on cutting-edge AI — contribute to projects with top AI research labs and directly influence how large language models understand infrastructure
- Complete schedule flexibility — work when you want, as much or as little as you want (10–40 hrs/week)
- Fully remote — work from anywhere, always
- Autonomy — no micromanagement, task-based work you can do independently
- Meaningful impact — your real-world engineering expertise makes AI smarter and safer for everyone
- Ongoing opportunity — strong performers are considered for contract extensions and additional projects
- Exposure to advanced LLMs — gain rare, behind-the-scenes insight into how frontier AI models are trained and evaluated
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