Senior Backend Engineer Remote (International)

Dover; India; Remote; INR 8,679,000 - 14,465,000; Part time

Job summary

Dover is seeking a Senior Backend Engineer to design and implement reinforcement learning environments for evaluating AI model proficiency. The role emphasizes building scalable cloud-based infrastructure, realistic distributed system scenarios, and robust validation tests.

Applicants should be strong in backend languages, DevOps, and cloud tools, with a focus on production-grade design, security, and maintainability.

Qualifications

• Proven backend languages expertise from listed stack.
• Experience designing scalable API backends and services.
• Familiarity with distributed systems and cloud concepts.

Responsibilities

• Design, develop, and test reinforcement learning environments for AI model evaluation.
• Create reproducible scenarios covering IAM, queues, storage, observability, and deployment pipelines.
• Develop deterministic validation tests and golden reference solutions.
• Craft intentionally defective variants to stress test AI model responses and recovery.
• Document architecture and operational flows for future reuse.
• Collaborate with leads to refine environment specs and acceptance criteria.

Skills

C++

Python

Rust

GoLang

JAVA

Javascript

Devops

Job description

Role Title:

Senior Backend Engineer

Role Type:

Contract (20 hrs per week)

Location:

Remote

Required Skills

• C++


• Python


• Rust


• Golang


• Java


• Javascript


• Devops

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

• 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.

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 20-hour task 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.