We are sharing a specialised consulting opportunity for experienced Senior Technical Architects with strong expertise in cloud infrastructure, distributed systems, platform engineering, DevOps, SRE, production architecture, and resilience engineering to contribute to an advanced AI training and cloud-infrastructure evaluation project.
Selected professionals will design realistic cloud-infrastructure tasks and reinforcement-learning environments that test an AI system's ability to design, deploy, secure, scale, troubleshoot, and recover production-grade systems. The work requires substantial hands-on production ownership, strong systems judgement, and the ability to create reproducible environments, deterministic tests, and rigorous reference solutions. No prior experience in AI is required.
Key Responsibilities
Cloud Architecture & Distributed Systems
- Design realistic infrastructure scenarios spanning 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 across performance, availability, security, and operational complexity
- Define clear system requirements and measurable success criteria
Infrastructure Environments & Validation
- Build reproducible, containerised technical environments
- Create reference implementations and intentionally defective variants
- Develop deterministic integration, load, security, failure-injection, deployment, and recovery tests
- Validate infrastructure configuration, topology, and runtime behaviour
- Support repeatable provisioning, execution, and teardown workflows
Security, Reliability & Operations
- 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
- Write automation or testing tools supporting environment setup and validation
AI Evaluation & Technical Review
- Create reinforcement-learning environments for multi-step infrastructure reasoning
- Build 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
Ideal Profile
- 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 IAM, private-networking, and service-security experience
- Strong observability, SLO, deployment, rollback, and disaster-recovery experience
- Ability to write infrastructure automation or testing tools
- Strong debugging skills in containerised environments
- Experience with Terraform or OpenTofu is advantageous
- Experience with AWS, Azure, GCP, Kubernetes, or multi-cloud environments is valuable
- Background in internal developer platforms, edge infrastructure, chaos engineering, fault injection, or resilience testing is beneficial
- No prior AI-training or model-evaluation experience is required
Engagement Details
- Independent contractor engagement
- Fully remote
- Displayed compensation range: $60–$130/hour
- Actual compensation structure is output-based, with payment made per task that meets project specifications
- Task completion time may vary depending on experience and workflow
- Minimum weekly submission requirements apply; the source does not specify the exact number of required tasks
- Work will involve cloud architecture, distributed systems, networking, IAM, observability, resilience testing, deployment workflows, and AI evaluation environments
- Roles are typically filled within approximately 48 hours
- Selected experts are expected to begin initial tasks within approximately 24–48 hours after onboarding
- Project scope, technical environments, benchmark requirements, and evaluation standards may evolve depending on project needs
- Work must be completed without using confidential or proprietary information belonging to any employer, client, cloud provider, software organisation, infrastructure environment, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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