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# DevOps / SRE Engineer (Kubernetes & Observability)

- **Company:** Argyll Info Tech Inc.,
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Contract:** Temporary to permanent
- **Skills:** System Configuration, Linux, DevOps, Python (Programming Language), Linux System Administration, Reliability Engineering, Prometheus, Software Engineering, Scripting, Cloud Platform System, System Availability, Grafana, Git, Containerization, Git Flow, Kubernetes, Software Version Control, Docker
- **Published:** October 16, 2026
- **Apply:** https://www.careerjet.com/jobad/us25a9b3a82cf18246b4b782eb3e95538f

## About the Role

Experience: 5+ years of professional experience in DevOps, Site Reliability Engineering (SRE), and infrastructure migrations.
Core Technologies:
Strong hands-on expertise in Kubernetes (deployment, configuration, and advanced troubleshooting).
Proficiency in Python for scripting, automation, and internal tool development.
Solid working knowledge of AWS cloud environments.
Observability: Hands-on configuration and troubleshooting experience with Prometheus, Grafana, and log/trace aggregators such as Loki.
Environments & Tools: Containerization via Docker, Linux administration, and Git-based workflows.

## Description

We are seeking an experienced DevOps / SRE Engineer with a strong background in migration, automation, and Kubernetes environments. In this role, you will play a key part in providing operational support for our telemetry and observability stacks, ensuring high availability, performance, and seamless monitoring across our infrastructure., Provide robust operational support for enterprise telemetry and observability stacks within a Kubernetes environment.
Design, develop, and maintain Python scripts and automation tools to streamline monitoring, support, and operational workflows.
Configure, monitor, and troubleshoot core observability platforms including Grafana, Prometheus, Loki, and Tempo.
Collaborate closely with DevOps, SRE, and cross-functional software development teams to guarantee optimal system performance and deep observability.
Manage containerized workloads using Docker and maintain efficient CI/CD pipelines.
Utilize Git-based version control workflows within a Linux-based operating environment.