Senior Backend Engineer | Remote - Contract

Xperteez Technology • ,

3h • Remote

About The Position

We are engaging Senior Backend Engineers to participate in an advanced project for a customer, focused on creating sophisticated Reinforcement Learning Environments for AI model training and evaluation. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

As an expert, you will create Reinforcement Learning Environments that test an AI model’s ability to design, deploy, troubleshoot, secure, scale, and recover production-grade cloud infrastructure. You will develop realistic scenarios involving distributed systems, networking, IAM, queues, durable storage, observability, rolling deployments, and disaster recovery, then build reproducible environments, deterministic validation tests, golden reference solutions, and intentionally defective variants.

Requirements

• C++
• Python
• Rust
• GoLang
• JAVA
• JavaScript
• DevOps

Nice To Haves

• 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.

Responsibilities

• 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.

What This Job Offers

• Job Type: Part-time
• Career Level: Senior
• Education Level: No Education Listed