Site Reliability Engineer
Job Description
This position is available in Stockholm and Uppsala.
About Scaleout Systems
Scaleout Systems develops AI/ML infrastructure solutions for edge-to-cloud environments, serving sectors including defense, industrial, and critical infrastructure.
The Role
Join the core development team as a hands-on SRE focusing on infrastructure reliability for AI/ML systems across edge-to-cloud environments. This is a hybrid role with offices in Stockholm and Uppsala.
What You'll Do
-
Design and operate infrastructure across cloud and edge environments
-
Build CI/CD pipelines for SDKs, control planes, and partner deployments
-
Implement monitoring, alerting, and telemetry frameworks for distributed systems
-
Harden security through automation of secrets management, patching, and vulnerability scanning aligned with NIS2 and AI Act requirements
-
Collaborate on deployment architectures scaling from research labs to regulated, air-gapped defense environments
-
Contribute infrastructure automation tools including Terraform modules and Helm charts
Requirements
-
Required: 3+ years in Site Reliability Engineering, DevOps, or Platform Engineering
-
Hands-on skills with Kubernetes and cloud infrastructure (Azure, AWS, GCP)
-
Proven CI/CD pipeline experience (GitHub Actions, GitLab CI)
-
Strong Linux systems administration and networking knowledge
-
Experience with monitoring stacks like Prometheus and Grafana
-
Security expertise including key management, TLS, and secrets handling
-
Ability to design resilient, highly available environments
-
Fluent English communication and documentation skills
-
Must be Swedish citizen eligible for security clearance
Nice to Have
-
AI/ML infrastructure or federated learning experience
-
Edge computing or air-gapped deployment familiarity
-
Compliance systems background (ISO 27001, NIS2)
-
Defense, industrial, or critical infrastructure sector experience
Skills & Technologies
Company Info
Scaleout Systems
Federated learning platform provider enabling secure, privacy-preserving machine learning across dis...
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Similar Opportunities
Job Description
This position is available in Stockholm and Uppsala.
About Scaleout Systems
Scaleout Systems develops AI/ML infrastructure solutions for edge-to-cloud environments, serving sectors including defense, industrial, and critical infrastructure.
The Role
Join the core development team as a hands-on SRE focusing on infrastructure reliability for AI/ML systems across edge-to-cloud environments. This is a hybrid role with offices in Stockholm and Uppsala.
What You'll Do
-
Design and operate infrastructure across cloud and edge environments
-
Build CI/CD pipelines for SDKs, control planes, and partner deployments
-
Implement monitoring, alerting, and telemetry frameworks for distributed systems
-
Harden security through automation of secrets management, patching, and vulnerability scanning aligned with NIS2 and AI Act requirements
-
Collaborate on deployment architectures scaling from research labs to regulated, air-gapped defense environments
-
Contribute infrastructure automation tools including Terraform modules and Helm charts
Requirements
-
Required: 3+ years in Site Reliability Engineering, DevOps, or Platform Engineering
-
Hands-on skills with Kubernetes and cloud infrastructure (Azure, AWS, GCP)
-
Proven CI/CD pipeline experience (GitHub Actions, GitLab CI)
-
Strong Linux systems administration and networking knowledge
-
Experience with monitoring stacks like Prometheus and Grafana
-
Security expertise including key management, TLS, and secrets handling
-
Ability to design resilient, highly available environments
-
Fluent English communication and documentation skills
-
Must be Swedish citizen eligible for security clearance
Nice to Have
-
AI/ML infrastructure or federated learning experience
-
Edge computing or air-gapped deployment familiarity
-
Compliance systems background (ISO 27001, NIS2)
-
Defense, industrial, or critical infrastructure sector experience
Skills & Technologies
Company Info
Scaleout Systems
Federated learning platform provider enabling secure, privacy-preserving machine learning across dis...
