高级后端工程师
Senior Backend Engineer
职位标题：高级后端工程师职位类型：合同 （每周20小时）地点：远程要求技能 · C++ · Python · Rust · Golang · Java · Javascript · Devops 在这个角色中，你将应用你的专业知识来帮助训练下一代人工智能系统。你的工作将塑造模型如何通过高质量的现实输入学习，推理和性能。没有先前的人工智能经验是重要的。作为一名专家，你将创建强化学习环境，测试一个人工智能模型设计，部署，解决问题，安全，扩展云层以及恢复生产基础设施的能力。你将开发涉及分布式系统，网络，IAM,排队，持久存储，可观测性，滚动部署和灾难恢复的现实场景，然后构建可复制环境，确定性验证测试，黄金参考解决方案和故意缺陷变体。工作范围 ·设计，开发和实施现实的云基础设施环境来评估 AI 模型在系统设计，部署和故障排除方面的能力。· 建立分布式系统，网络，身份和访问管理 (IAM),消息队列，持续存储，可观察性，滚动部署以及灾难恢复的详细和可复制性的场景。·开发确定验证测试和黄金参考解决方案以确保增强学习环境的可靠性和准确性。· 制作故意缺陷变体和失败场景以严格检查人工智能模型响应和恢复策略。·为所有发达环境记录架构，边缘案例和运营流程，确保未来使用清晰度和复制性。· 与技术领导者和项目参与者合作，以不断完善环境规范和接受标准。· 应用 DevOps 和基础设施自动化实践，为基于云的系统评估提供可扩展，安全和可维护解决方案。首选资格 · 凭借 C++,Python,Rust,GoLang,JavaScript 等后端编程语言的经验。·与 DevOPS,云基础设施，CI/CD 管道和自动化工具有强大的实际经验。• 在生产级环境中架构，扩展和保护分布式系统的能力。· 深入了解网络，IAM,排队，耐用存储和灾难恢复概念
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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.
Process:
- Apply to the role, filling out the screening questions
- Complete AI interview (aprox. 30 minutes), reviewed by recruiters
- Hiring Manager review
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.
Originally posted on Himalayas