We are sharing a specialised consulting opportunity for experienced Senior Backend Engineers with strong expertise in backend development, distributed systems, cloud infrastructure, DevOps, networking, IAM, observability, and production-grade systems engineering to contribute to an advanced AI training and reinforcement-learning environment project.

Selected professionals will create realistic reinforcement-learning environments that test advanced AI systems on production infrastructure challenges involving system design, deployment, troubleshooting, security, scalability, and recovery. The work requires strong backend and infrastructure engineering judgement, reproducible technical environments, deterministic validation, and robust reference solutions. No prior experience in AI is required.

Key Responsibilities

Reinforcement Learning Environment Development

• Design realistic technical environments for evaluating AI systems
• Create infrastructure scenarios involving deployment, troubleshooting, scaling, and recovery
• Define clear technical requirements, constraints, and expected outcomes
• Build reproducible environments suitable for deterministic evaluation
• Develop scenarios that reflect authentic production engineering challenges

Distributed Systems & Cloud Infrastructure

• Design scenarios involving production-grade distributed systems
• Work across networking, service communication, queues, and durable storage
• Evaluate infrastructure architecture for reliability, scalability, and resilience
• Apply sound systems-design principles to realistic cloud environments
• Incorporate operational failure modes into environment design

Identity, Security & Access Control

• Develop scenarios involving Identity and Access Management
• Evaluate authentication, authorisation, permissions, and access-control decisions
• Incorporate infrastructure security considerations into technical environments
• Identify common configuration or security failure modes
• Ensure environments reflect realistic production-security requirements

Validation & Golden Reference Solutions

• Develop deterministic validation tests for technical environments
• Create golden reference solutions demonstrating correct implementation
• Define reliable acceptance criteria for AI-generated solutions
• Ensure environments produce consistent and reproducible evaluation outcomes
• Validate both expected behaviour and failure conditions

Failure Scenarios & Recovery Testing

• Create intentionally defective environment variants
• Design failure scenarios involving infrastructure, networking, storage, or deployment issues
• Test recovery strategies and troubleshooting approaches
• Evaluate disaster-recovery and fault-tolerance behaviours
• Ensure scenarios meaningfully test operational engineering judgement

DevOps & Infrastructure Automation

• Apply DevOps practices to environment creation and maintenance
• Work with CI/CD pipelines and infrastructure automation
• Develop scalable and repeatable deployment workflows
• Incorporate observability and operational monitoring where relevant
• Build maintainable systems suitable for repeated technical evaluation

Technical Documentation & Collaboration

• Document architecture, operational flows, assumptions, and edge cases
• Produce clear technical explanations supporting environment reproducibility
• Collaborate with technical leads and project participants
• Refine specifications and acceptance criteria based on feedback
• Communicate technical trade-offs and design decisions clearly

Ideal Profile

• Strong professional backend-engineering experience
• Proven expertise in one or more of C++, Python, Rust, GoLang, Java, or JavaScript
• Strong practical experience with DevOps and cloud infrastructure
• Experience with CI/CD pipelines and infrastructure automation
• Demonstrated ability to architect, scale, and secure distributed systems
• Deep understanding of networking concepts
• Strong knowledge of Identity and Access Management
• Experience with message queues and durable storage systems
• Familiarity with observability, monitoring, and operational diagnostics
• Strong understanding of rolling deployments and disaster recovery
• Experience troubleshooting production-grade systems
• Ability to design deterministic tests and reproducible technical environments
• Strong technical documentation and communication skills
• No prior AI-training or model-evaluation experience is required

Engagement Details

• Independent contractor engagement
• Fully remote
• Expected commitment: approximately 20 hours per week
• Displayed compensation range: $50–$100/hour
• Actual compensation structure is output-based, with payment made per task that meets project specifications
• Task completion time may vary depending on individual experience and workflow
• Minimum weekly submission requirements apply; the source does not specify the exact number of required tasks
• Work will involve reinforcement-learning environments, backend engineering, distributed systems, DevOps, cloud infrastructure, deterministic testing, and golden reference solutions
• Strong systems-engineering and production-infrastructure judgement are central to this engagement
• Screening includes an approximately 30-minute AI interview followed by hiring-manager review
• 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, workload, infrastructure scenarios, and evaluation standards may evolve depending on project requirements
• Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, 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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