Senior Backend Engineer

Artha Nexgen; Northern (KY); Hybrid; USD 90,000 - 120,000; Full time

Job summary

Artha Nexgen is seeking Senior Backend Engineers to contribute to an advanced Reinforcement Learning Environments project, building testable cloud infrastructure for AI model training and evaluation.

You will design realistic distributed systems with IAM, queues, durable storage and observability, create reproducible environments, deterministic tests, and fail-safe variants to rigorously assess model performance.

Qualifications

• 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, IAM, message queues, persistent storage, observability, rolling deployments, and disaster recovery.
• Develop deterministic validation tests and golden reference solutions to ensure reliability and accuracy of reinforcement learning environments.
• Produce intentionally defective variants and failure scenarios to rigorously test AI model responses and recovery strategies.
• Document 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.

Skills

DevOps

Cloud infrastructure

CI/CD

Automation tools

Distributed systems

Networking

IAM

Observability

Job description

backend programming DevOps cloud infrastructure distributed systems observability

This job requires a minimum of 3 years of experience.

About the Job

Location: Remote

micro1 is 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.

Scope of Work

• 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.

Preferred Qualifications

• 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.

Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert's experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24-48 hours of completing onboarding.