Cloud Infrastructure Task Author

About OpenTrain

OpenTrain is the centralized platform where people build careers in AI training and data labeling. We help freelancers discover projects, consolidate proof-of-work, and grow a visible portfolio that demonstrates real engineering experience for future opportunities.

Why AI training work matters

AI models learn from high-quality human examples and engineering feedback. Contributing to AI training means shaping how systems understand architecture, operations, and reliability—work that is remote, flexible, and often accessible without prior annotation experience.

• Work remotely and on a flexible schedule to fit studies, other jobs, or family commitments.
• Contribute directly to how AI systems reason about real-world infrastructure and failure modes.

Role overview

As a Cloud Infrastructure Task Author you will design realistic, measurable cloud infrastructure tasks and build reproducible environments that evaluate deployment, security, scalability, observability, and recovery skills. Your deliverables include reference solutions, intentionally defective variants, deterministic tests, and documentation that make tasks usable for training and evaluating models.

• Create scenarios across distributed systems, networking, IAM, queues, durable storage, observability, rolling deployments, and disaster recovery.
• Build containerized reproducible environments and deterministic validation tests.
• Produce reference solutions, failure-injected variants, and clear acceptance criteria.

What you'll do day to day

• Design cloud infrastructure tasks that probe design, deployment, troubleshooting, security, scalability, and recovery skills.
• Build reproducible, containerized environments with valid reference solutions and intentionally defective variants.
• Define measurable requirements for configuration, topology, and runtime behavior.
• Develop deterministic integration, load, security, failure-injection, deployment, and recovery tests.
• Debug environments, document technical decisions, and review tasks created by other experts.

Requirements

The role requires strong, hands-on infrastructure judgment and the ability to author both working and defective task variants. The listing marks experience level as Entry level, but the required skills and responsibilities call for senior hands-on experience in production platform ownership and systems engineering.

• Senior-level experience in cloud infrastructure, platform engineering, DevOps, systems engineering, or SRE.
• Personal ownership of a production platform and strong hands-on infrastructure judgment.
• Practical knowledge of distributed systems, scalable APIs, queues, autoscaling, durable storage, and partial-failure scenarios.
• Experience with IAM, private networking, least-privilege access, service-to-service security, observability, SLOs, rollback strategies, and disaster recovery.
• Ability to write infrastructure automation or testing tools and debug containerized environments using a relevant programming language.
• Familiarity with Terraform or OpenTofu, AWS, Azure, GCP, Kubernetes, chaos engineering, fault injection, local cloud emulators, or resilience testing is valuable.

Schedule, pay, and logistics

This is a remote contractor role with flexible scheduling. OpenTrain typically uses a part-time workload estimate for external hourly projects.

• Time requirement: 20+ hours/week (part-time contractor).
• Pay: hourly, USD $40–$100/hr (listing includes an upper-rate reference of $100/hr).
• Contractor engagement — you will deliver output: tasks, environments, tests, and documentation.

Who should apply and how it works

Apply if you have deep, practical cloud infrastructure experience and enjoy turning real engineering problems into reproducible, testable tasks. Task authorship is output-focused: quality of environments, determinism of tests, and clarity of documentation are core deliverables.

• Ideal candidates: SREs, platform engineers, senior DevOps engineers, or systems engineers with production ownership.
• You will create work artifacts (environments, tests, reference solutions) that train and evaluate AI systems on infrastructure reasoning.
• Labeling/data type context: tasks will generate TEXT-based training inputs and support DATA_COLLECTION and EVALUATION_RATING workflows.

Next steps to apply

Create a free OpenTrain profile, complete your experience summary and portfolio items, and submit your application. Include examples of platforms or production systems you have owned and any sample reproducible environments or automation scripts you can share.