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. About the Project A fast-growing tech company is building an infrastructure layer for modern AI workloads — a globally distributed platform that provides scalable, cost-efficient, and reliable access to GPU computing resources. The platform enables customers to run production-level inference workloads across a diverse network of providers, offering flexibility, performance, and resilience required for real-world AI applications. Since its launch, the company has demonstrated strong traction, securing a significant Series A investment and achieving multi-million ARR within its first year of operation. As both customer demand and platform scale continue to expand, the team is actively growing its infrastructure capabilities to support the next stage of development. About the Role We are looking for a strong SRE / DevOps / Infrastructure Engineer to help scale and operate a distributed AI-focused infrastructure platform. The system combines a cloud-based control layer (running on AWS, including EKS and managed MySQL) with a large fleet of GPU-powered nodes distributed across multiple external providers. These components are connected via a custom networking layer to ensure high availability and performance for production workloads. Workloads are orchestrated with Kubernetes, while observability is built around Prometheus, Grafana, Loki, Jaeger, and OpenTelemetry, covering metrics, logging, and tracing across the platform. While the control layer is relatively lightweight and cloud-native, the GPU infrastructure introduces additional complexity. It spans different providers and environments, often resembling distributed on-premise setups rather than standard cloud infrastructure, requiring a deeper understanding of networking, reliability, and systems behavior at scale. This is a hands-on role focused on solving real infrastructure challenges across Kubernetes, networking, observability, and production operations. You will join a small, high-impact infrastructure team (currently a couple of engineers) that is actively growing as the platform and customer base continue to expand. The goal is to strengthen the core infrastructure early and support further scaling. 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 - Work closely with engineers across time zones using clear asynchronous communication and handoff practices, especially through Slack - Help expand Europe-based infrastructure coverage to support sustainable operations outside US business hours

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. About the Project A fast-growing tech company is building an infrastructure layer for modern AI workloads — a globally distributed platform that provides scalable, cost-efficient, and reliable access to GPU computing resources. The platform enables customers to run production-level inference workloads across a diverse network of providers, offering flexibility, performance, and resilience required for real-world AI applications. Since its launch, the company has demonstrated strong traction, securing a significant Series A investment and achieving multi-million ARR within its first year of operation. As both customer demand and platform scale continue to expand, the team is actively growing its infrastructure capabilities to support the next stage of development. About the Role We are looking for a strong SRE / DevOps / Infrastructure Engineer to help scale and operate a distributed AI-focused infrastructure platform. The system combines a cloud-based control layer (running on AWS, including EKS and managed MySQL) with a large fleet of GPU-powered nodes distributed across multiple external providers. These components are connected via a custom networking layer to ensure high availability and performance for production workloads. Workloads are orchestrated with Kubernetes, while observability is built around Prometheus, Grafana, Loki, Jaeger, and OpenTelemetry, covering metrics, logging, and tracing across the platform. While the control layer is relatively lightweight and cloud-native, the GPU infrastructure introduces additional complexity. It spans different providers and environments, often resembling distributed on-premise setups rather than standard cloud infrastructure, requiring a deeper understanding of networking, reliability, and systems behavior at scale. This is a hands-on role focused on solving real infrastructure challenges across Kubernetes, networking, observability, and production operations. You will join a small, high-impact infrastructure team (currently a couple of engineers) that is actively growing as the platform and customer base continue to expand. The goal is to strengthen the core infrastructure early and support further scaling. 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 - Work closely with engineers across time zones using clear asynchronous communication and handoff practices, especially through Slack - Help expand Europe-based infrastructure coverage to support sustainable operations outside US business hours

• Build and set up new development tools and infrastructure. • Deploy product updates and fixes accurately, efficiently and securely. • Ensure systems are safe and secure against cybersecurity threats. • Work with Software Engineers to ensure that development follows established processes and works as intended. • Automate and improve development and release processes. • Build tools to reduce occurrences of errors and improve customer experience. • Investigate, identify and resolve technical issues. • Plan out projects and be involved in project management decisions. • Provide Level 2 technical support. • Develop software to integrate with internal back-end systems. • Perform root cause analysis for production issues. • Design procedures for system troubleshooting and maintenance.

• Design, develop, and maintain scalable backend services using Node.js • Build and manage API integrations and external system connections • Work with Azure cloud infrastructure for deployment and scaling • Implement and manage event-driven systems, including geolocation-based features • Develop and optimize push notification orchestration systems • Contribute to DevOps processes, including CI/CD, monitoring, and infrastructure improvements • Ensure system reliability, performance, and security • Collaborate with cross-functional teams (product, hardware, and software) • Make independent architectural decisions and drive technical solutions