Senior Technical Architect for AI Model Training [Remote]

In this role, you will leverage your platform engineering expertise to contribute to the training of next-generation AI systems. Your efforts will significantly influence how models learn, reason, and perform by providing high-quality, real-world engineering input. Key Responsibilities

• Create realistic cloud infrastructure tasks that encompass distributed systems, networking, security, scalability, and reliability.
• Build reproducible, containerized environments with valid reference solutions and intentionally defective variants.
• Define measurable requirements across infrastructure configuration, deployed 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.

• Senior-level experience in technical architecture, cloud infrastructure, platform engineering, DevOps, systems engineering, or SRE, including personal ownership of a production platform.
• Strong knowledge of distributed systems, scalable APIs, queues, autoscaling, durable storage, and partial-failure scenarios.
• Practical experience with IAM, private networking, least-privilege access, and service-to-service security.
• Experience with observability, measurable SLOs, rolling deployments, rollback strategies, and disaster recovery.
• Ability to write infrastructure automation or testing tools and debug containerized environments using a relevant programming language.

• Experience with Terraform or OpenTofu.
• Experience with AWS, Azure, GCP, Kubernetes, or multi-cloud infrastructure.
• Experience building internal developer platforms, edge infrastructure, or shared platform services.
• Experience with chaos engineering, fault injection, local cloud emulators, or resilience testing.
• Experience creating technical evaluations, automated grading systems, or AI environments is helpful but not required.

This is a contractor position, fully remote. Experts must submit a minimum number of tasks per week, with compensation structured on an output-based model, paying per task that meets project specifications.

Hourly compensation ranges from $40 to $100, depending on the expert''s experience and workflow.

No prior experience in AI is required; however, domain knowledge and hands-on production experience are essential.