Remote | Senior Technical Architect — $60–$130/hour
About The Position
This is a remote, independent-contractor consulting opportunity for an experienced Senior Technical Architect contributing to an advanced AI training and cloud-infrastructure evaluation project. The work involves designing realistic cloud infrastructure tasks and reinforcement-learning environments to evaluate whether an AI system can design, deploy, secure, scale, troubleshoot, and recover production-grade systems. It calls for substantial hands-on production ownership, sound systems judgment, and the ability to create reproducible environments, deterministic tests, and rigorous reference solutions. Prior AI experience is not required. The engagement is paid per task that meets project specifications, with a displayed compensation range of $60–$130 per hour; actual compensation is output-based. Task completion time may vary by experience and workflow, and minimum weekly submission requirements apply, though the exact task count is not specified. Project scope, technical environments, benchmark requirements, and evaluation standards may evolve. Selected experts are expected to begin initial tasks approximately 24–48 hours after onboarding. Work must not use confidential or proprietary information belonging to an employer, client, cloud provider, software organization, infrastructure environment, or other third party. The opportunity is available through 24-MAG LLC, which connects experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. Applicant information may be processed for recruitment and opportunity matching in accordance with the company's Privacy Policy.
Requirements
- Senior-level experience in technical architecture, cloud infrastructure, platform engineering, DevOps, systems engineering, or SRE.
- Demonstrated ownership of production infrastructure or a production platform.
- Strong knowledge of distributed systems, scalable APIs, queues, autoscaling, and durable storage.
- Practical experience with IAM, private networking, and service security.
- Strong experience with observability, SLOs, deployment, rollback, and disaster recovery.
- Ability to write infrastructure automation or testing tools.
- Strong debugging skills in containerised environments.
Nice To Haves
- Experience with Terraform or OpenTofu.
- Experience with AWS, Azure, GCP, Kubernetes, or multi-cloud environments.
- Background in internal developer platforms, edge infrastructure, chaos engineering, fault injection, or resilience testing.
Responsibilities
- Design realistic infrastructure scenarios involving distributed systems, networking, security, scalability, and reliability.
- Evaluate architectures involving scalable APIs, queues, durable storage, autoscaling, and service coordination.
- Model partial failures, degraded services, and realistic production constraints; assess trade-offs in performance, availability, security, and operational complexity.
- Define clear system requirements and measurable success criteria.
- Build reproducible, containerised technical environments, reference implementations, and intentionally defective variants.
- Develop deterministic integration, load, security, failure-injection, deployment, and recovery tests.
- Validate infrastructure configuration, topology, and runtime behaviour, and support repeatable provisioning, execution, and teardown workflows.
- Design scenarios involving IAM, least privilege, private networking, and service-to-service security.
- Incorporate logging, metrics, tracing, SLOs, and operational telemetry; evaluate rolling deployments, rollback strategies, disaster recovery, and resilience.
- Develop realistic troubleshooting and incident scenarios, and write automation or testing tools for environment setup and validation.
- Create reinforcement-learning environments for multi-step infrastructure reasoning, including golden solutions and defective or adversarial variants.
- Review peer-created tasks for ambiguity, unrealistic assumptions, or validation gaps; improve benchmark difficulty, reproducibility, and grading reliability.
- Maintain strong engineering standards across project deliverables.
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What This Job Offers
Career Level
Senior
Education Level
No Education Listed
