About the Role
Senior Platform Engineer Remote – Are you an experienced Platform Engineer or DevOps Leader ready to shape the future of Artificial Intelligence? EliteCareers is partnering with innovative AI initiatives to recruit senior cloud infrastructure experts. In this high-impact remote contract role, you will leverage your real-world systems architecture expertise to design evaluation environments and train next-generation AI models.
No prior AI or machine learning experience is required. We are seeking a Senior Platform Engineer Remote, seasoned systems specialists who possess hands-on production experience in building, scaling, and repairing modern cloud platforms.
Key Responsibilities
Design Complex RL Environments: Construct realistic Reinforcement Learning (RL) scenarios spanning distributed systems, IAM, cloud networking, durable storage, and resilience.
Build Reproducible Testbeds: Develop fully containerized infrastructure setups featuring golden-path reference solutions alongside intentionally defective variants.
Implement Deterministic Validation: Write robust integration, failure-injection, load, and security tests to measure AI reasoning and execution.
Ensure Technical Excellence: Debug cloud test environments, document platform decisions, and conduct peer code reviews to maintain high evaluation standards.
Simulate Production Outages: Build real-world chaos engineering, rolling deployment, and disaster recovery scenarios to test AI problem-solving capabilities.
Required Qualifications
Senior Systems Experience: Proven track record in Platform Engineering, DevOps, Cloud Infrastructure, or Site Reliability Engineering (SRE) managing production-grade platforms.
Distributed Systems Architecture: Deep understanding of microservices, cloud networking, private subnets, least-privilege IAM, and autoscaling.
Infrastructure Automation: Proficiency in writing infrastructure automation scripts or testing tools using modern programming languages.
Observability & Resilience: Hands-on expertise with SLO monitoring, rolling updates, rollback procedures, and fault-tolerant architectures.
Containerization: Demonstrable capability in debugging and running containerized runtime environments.
Preferred Skills
High proficiency with Terraform, OpenTofu, or infrastructure-as-code (IaC) tooling.
Direct multi-cloud experience (AWS, GCP, Azure) and Kubernetes orchestration.
Experience with chaos testing, fault injection, and local cloud emulators.
Prior experience designing technical assessments, internal developer platforms (IDP), or automated grading pipelines.
Application Process & Compensation
Quick Hiring Timeline: Applications are evaluated rapidly, with candidates expected to onboard and begin within 24–48 hours of selection.
Interview Process: Initial Application Screening $\rightarrow$ 30-minute AI Technical Interview $\rightarrow$ Final Review.
Compensation Structure: Output-based compensation per verified completed task, offering flexibility based on your technical throughput. Minimum weekly submission thresholds apply.