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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
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
- 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
- Strong operational judgment: able to troubleshoot independently, respond calmly to incidents, and improve systems without constant direction
- Comfortable working in a fast-moving startup where infrastructure, product, and customer demands are changing quickly
- Clear communicator who can work effectively in an async environment and handle shift handoffs cleanly
- 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
Key Skills
Ranked by relevance
ai
kubernetes
cloud
prometheus
grafana
devops
loki
aws
infrastructure as code
high availability
ai tools
mysql
linux
eks
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- Posted
- Apr 01, 2026
- Type
- Full-time
- Level
- Entry
- Location
- Spain
- Company
- Intetics
Industries
IT Services
IT Consulting
Categories
Other
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