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. No prior experience in AI is required.
Key Responsibilities
Backend, Distributed Systems & Infrastructure
- Design realistic technical environments involving backend services, distributed systems, networking, queues, and durable storage
- Create production-style scenarios covering deployment, scaling, troubleshooting, and recovery
- Evaluate architecture for reliability, scalability, resilience, and operational correctness
- Incorporate realistic failure modes and infrastructure constraints
- Apply strong systems-design judgement across cloud environments
Security, DevOps & Reliability
- Develop scenarios involving IAM, authentication, authorisation, permissions, and access control
- Work with CI/CD, infrastructure automation, rolling deployments, and operational workflows
- Incorporate observability, monitoring, and diagnostic requirements
- Design fault-tolerance and disaster-recovery scenarios
- Identify common production configuration, networking, and security failures
Validation & Environment Quality
- Build reproducible environments with deterministic validation
- Create golden reference solutions and objective acceptance criteria
- Develop defective variants that test troubleshooting and recovery skills
- Validate expected behaviour, failure conditions, and edge cases
- Document architecture, assumptions, operational flows, and technical trade-offs clearly
Ideal Profile
- Strong professional backend-engineering experience
- Expertise in one or more of C++, Python, Rust, Go, 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 and Identity and Access Management
- Experience with message queues, durable storage, observability, and production diagnostics
- Strong knowledge of rolling deployments, fault tolerance, 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 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
- Screening includes an approximately 30-minute AI interview followed by hiring-manager review
- Roles are typically filled within approximately 48 hours, with initial tasks expected 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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