Senior DevOps Engineer for Distributed AI Infrastructure

About the Role

Intetics Inc., a global technology company providing custom software application development, distributed professional teams, software product quality assessment, and "all-things-digital" solutions, is seeking a highly skilled and experienced Senior DevOps Engineer to join our dynamic team on a full-time basis. This Senior DevOps Engineer remote position offers the opportunity to work on cutting-edge technology in a fast-paced environment.

What You'll Do

• Build, operate, and improve the infrastructure powering Parasail's distributed inference platform.
• Own reliability, scalability, and operational excellence across AWS-based control planes and our multi-provider GPU fleet.
• Design and maintain the networking layer connecting control planes, Kubernetes clusters, and geographically distributed GPU hosts.
• Operate and improve Kubernetes-based inference orchestration, primarily on EKS.
• Manage deployments and infrastructure changes using Helm, FluxCD, and Terraform.
• Improve observability across the platform using metrics, logs, traces, dashboards, and alerting built on Prometheus, Grafana, Loki, Jaeger, and OpenTelemetry.
• Tune alerts, improve runbooks, and strengthen operational readiness as the system scales.
• Respond to production issues, perform root cause analysis, and implement durable fixes.

Requirements

• 5+ years of experience in SRE, DevOps, platform engineering, or infrastructure engineering.
• Strong production experience with networking and Kubernetes.
• Experience operating AWS infrastructure in production, especially EKS.
• Strong hands-on experience managing Linux hosts, clusters, and distributed systems in environments that are not fully abstracted by a major cloud provider.
• Experience with Prometheus, Grafana, Loki, Jaeger, and OpenTelemetry.
• Experience with deployment and GitOps workflows using tools such as Helm and FluxCD.
• Experience with infrastructure as code, ideally Terraform.
• Familiarity with alert tuning, runbook development, and practical incident management in production systems.

Nice to Have

• Experience with AI inference, ML infrastructure, or adjacent high-performance distributed systems.
• Experience operating heterogeneous GPU fleets, bare-metal infrastructure, or multi-provider compute environments.
• Experience using AI tools productively in engineering workflows.

What We Offer

• Competitive salary and relocation support.
• Flexible working hours and remote work opportunities.
• Dynamic and innovative work environment.
• Professional development and growth opportunities.
• Access to cutting-edge technologies and tools.