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# Senior DevOps Engineer

- **Company:** Radar, Inc.
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $130,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Android Software Development, Systems Engineering, Audit Trail, C++ (Programming Language), Continuous Integration, Software Debugging, Linux, DevOps, Distributed Systems, Firmware, Github, Gradle, Python (Programming Language), Machine Learning, Octopus Deploy, Software Construction, Systems Integration, Delivery Pipeline, Build Management, Yocto, Kubernetes, Machine Learning Operations, Terraform, Golang
- **Published:** May 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=79aa7fdabf1e2a53

## About the Role

Do you have experience in Tooling?, We are seeking a Senior DevOps Engineer with 5+ years of experience to join our dynamic team, helping drive the development, deployment, and operation of cloud, mobile, IoT, embedded, and edge compute solutions. You'll work across a wide technical landscape and play a critical role in shaping our infrastructure, CI/CD, and developer experience.

This is a hybrid role based in our Seattle office, requiring a minimum of three days per week in-office., * Experience integrating iOS/Android mobile build pipelines into larger CI/CD workflows.

 * Background with IoT device regression systems, firmware pipelines, or embedded testing frameworks.
 * Knowledge of monitoring and logging solutions for distributed and embedded environments.

## Description

* Design, implement, and maintain robust CI/CD pipelines leveraging GitHub Actions building software using Gradle which is delivered using Argo CD, Kargo and modern DevOps tooling.
 * Manage and scale containerized applications across cloud and edge environments using Kubernetes.
 * Build and manage infrastructure using Terraform, applying industry best practices for IaC.
 * Support build, packaging, and deployment workflows for services written in Java, Go, Python, and C++.
 * Collaborate with embedded and systems engineering teams working with Xilinx, Yocto, and other embedded OS environments.
 * Automate and optimize ML Ops workflows for machine learning deployment and validation.
 * Improve reliability, scalability, and security across systems spanning mobile, cloud, IoT, and edge compute.
 * Ensure DevOps systems and practices meet SOC 2 requirements, including access controls, audit logging, and change management across build and deployment infrastructure.
 * Troubleshoot and resolve complex issues across distributed systems, including deep debugging within Linux and networking layers.


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