Software Engineer | Remote

Crossing Hurdles; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Crossing Hurdles is seeking a seasoned DevOps/Cloud Architect to design, develop, and implement realistic cloud environments for evaluating AI model proficiency. You will craft scenarios around distributed systems, networking, IAM, and disaster recovery to stress-test models.

You will produce deterministic validation tests and golden references for reinforcement learning environments, create defective variants to test recovery strategies, and document architectures and operational flows for

Qualifications

• Strong practical experience with DevOps, cloud infrastructure, CI/CD pipelines and automation tools.
• 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.
• Create detailed scenarios involving distributed systems, networking, IAM, and disaster recovery.
• Develop deterministic validation tests and golden reference solutions for reinforcement learning environments.
• Produce intentionally defective variants to test AI model responses and recovery strategies.
• Document architecture, edge cases, and operational flows for developed environments.
• Collaborate with technical leads to refine environment specifications and acceptance criteria.
• Apply DevOps practices to deliver scalable, secure, and maintainable solutions.

Skills

DevOps

Cloud infrastructure

CI/CD pipelines

Automation

Distributed systems

Security

Networking

IAM

Queues

Durable storage

Disaster recovery

Job description

• Design, develop, and implement realistic cloud infrastructure environments to evaluate AI model proficiency.
• Create detailed scenarios involving distributed systems, networking, IAM, and disaster recovery.
• Develop deterministic validation tests and golden reference solutions for reinforcement learning environments.
• Produce intentionally defective variants to test AI model responses and recovery strategies.
• Document architecture, edge cases, and operational flows for developed environments.
• Collaborate with technical leads to refine environment specifications and acceptance criteria.
• Apply DevOps practices to deliver scalable, secure, and maintainable solutions.

Requirements

• 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.