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. #### :
Required
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. #### Preferred:
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. ### WHAT YOU'LL DO
In your first 30 days, you will:
Gain a strong understanding of the existing build, cloud, and deployment systems. - Fix 2–3 defects or small features that improve reliability, reduce friction, or enhance developer workflows. #### In your first 60 days, you will:
Ramp into additional build, embedded, and regression systems. - Begin asserting ownership over IoT regression infrastructure and ML Ops pipelines. - Contribute to Terraform-based infrastructure and IaC workflows. #### In your first 90 days, you will:
Remove or significantly reduce dependencies on Cloud Run / Cloud Functions, migrating workloads to Kubernetes. - Play a key role in enabling ephemeral development environments. - Take ownership of cloud cost visibility and deliver a reduction plan informed by usage analysis, architectural recommendations, and workload migration opportunities
*At RADAR, your base pay is one part of your total compensation package. The expected base salary range for this position is $130,000 - $180,000. Individual pay is determined by work location and additional factors, including job-related skills, experience and relevant education or training.*You will also be eligible to receive other benefits including: equity, comprehensive medical and dental coverage, life and disability benefits, 401k plan, flexible time off, and paid parental leave. The pay range listed for this position is a good faith and reasonable estimate of the range of possible base compensation at the time of posting.
Research has shown that women & underrepresented minorities are more likely to read lists of requirements and consider themselves unqualified if they don't meet every single one. This list represents what we're ideally looking for, but everyone has unique strengths & weaknesses, and we hire for strength & potential, not lack of weakness.
Use of artificial intelligence or a LLM such as ChatGPT during the interview process will be grounds for rejection of your application process.
