[Hiring] Senior Platform Engineer @24-MAG

Role Description

We are sharing a specialised consulting opportunity for experienced Senior Platform Engineers with strong expertise in cloud infrastructure, distributed systems, platform engineering, DevOps, SRE, production infrastructure, and resilience engineering to contribute to an advanced AI training and cloud-infrastructure evaluation project. Selected professionals will design realistic infrastructure tasks and reinforcement-learning environments that test an AI system's ability to deploy, secure, scale, troubleshoot, and recover production-grade systems. The role requires substantial hands-on production ownership and strong systems judgement. No prior experience in AI is required.

Key Responsibilities

• Cloud Infrastructure & Systems Design
  • Design realistic tasks involving distributed systems, networking, security, scalability, and reliability.
  • Evaluate architecture across compute, storage, networking, queues, APIs, and service layers.
  • Incorporate production constraints, partial failures, and degraded-service conditions.
  • Define clear technical success criteria and realistic system topologies.
  • Apply production experience to strengthen benchmark realism.
• Environment Development & Validation
  • Build reproducible, containerised infrastructure environments.
  • Create reference implementations and intentionally defective variants.
  • Develop deterministic integration, load, security, deployment, and recovery tests.
  • Validate infrastructure configuration, topology, and runtime behaviour.
  • Support repeatable provisioning, execution, and teardown workflows.
• Reliability, Security & Operations
  • Design scenarios involving IAM, least privilege, private networking, and service-to-service security.
  • Incorporate observability, logging, metrics, tracing, and measurable SLOs.
  • Evaluate rolling deployments, rollback strategies, disaster recovery, and resilience.
  • Build troubleshooting tasks based on realistic infrastructure failures.
  • Develop automation and testing utilities for environment setup and validation.
• AI Evaluation & Technical Review
  • Create reinforcement-learning environments for multi-step infrastructure reasoning.
  • Define measurable requirements and golden reference solutions.
  • Review peer-created tasks for ambiguity, unrealistic assumptions, or validation gaps.
  • Improve reproducibility, benchmark difficulty, and grading reliability.
  • Maintain strong engineering standards across project deliverables.

Qualifications

• Senior-level experience in 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, 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 infrastructure 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 reinforcement-learning 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.