Senior Backend Engineer

• Create Reinforcement Learning Environments that test an AI model’s ability to design, deploy, troubleshoot, secure, scale, and recover production-grade cloud infrastructure.
• Develop realistic scenarios involving distributed systems, networking, IAM, queues, durable storage, observability, rolling deployments, and disaster recovery.
• Design, develop, and implement realistic cloud infrastructure environments to evaluate AI model proficiency in systems design, deployment, and troubleshooting.
• Create detailed and reproducible scenarios involving distributed systems, networking, Identity and Access Management (IAM), message queues, persistent storage, observability, rolling deployments, and disaster recovery.
• Develop deterministic validation tests and golden reference solutions to ensure the reliability and accuracy of reinforcement learning environments.
• Produce intentionally defective variants and failure scenarios to rigorously test AI model responses and recovery strategies.
• Document the architecture, edge cases, and operational flows for all developed environments, ensuring clarity and reproducibility for future use.
• Collaborate with technical leads and project participants to iteratively refine environment specifications and acceptance criteria.
• Apply DevOps and infrastructure automation practices to deliver scalable, secure, and maintainable solutions for cloud-based systems evaluation.

• Proven expertise with backend programming languages, such as C++, Python, Rust, GoLang, JAVA, or JavaScript.
• Strong practical experience with DevOps, cloud infrastructure, CI/CD pipelines, and automation tools.
• Demonstrated ability to architect, scale, and secure distributed systems in production-grade environments.
• Deep understanding of networking, IAM, queues, durable storage, and disaster recovery concepts.

Project and contracting process: micro1. Applications continue on the provider's website.