Senior DevOps Engineer

At RADAR, we're transforming the way the world thinks about physical retail. RADAR has raised over $104M from top investors, retailers, and strategics and works with some of the world's retail brands including American Eagle and Gap. We’re building the future of in-store experience where every product and every person can be precisely located in real time.

Our platform combines RFID and AI to unlock hyper-accurate product visibility and automation at scale. From real-time inventory tracking to seamless checkout experiences, our technology empowers some of the world’s largest retailers to streamline operations, reduce loss, and elevate both employee and customer experiences.

We’re a fast-growing, mission-driven startup where bold ideas, collaboration, and impact are at the core of everything we do. Join us as we reshape the physical world with digital precision, starting with retail and expanding far beyond!

Mission-Driven: We're transforming retail with cutting-edge technology and building something that truly matters.

Collaborative Team: We thrive on curiosity, shared goals, and solving complex problems together.

High Impact: You’ll make meaningful contributions from day one and help shape the future of our product and company.

Clear Communication: We value honesty, humility, and respectful dialogue—everyone’s voice matters.

Balanced Lives: We work hard, but not at the expense of well-being. We respect time, boundaries, and life outside of work.

Diverse Perspectives: We believe better ideas come from diverse backgrounds, experiences, and viewpoints.

Empathy-Driven Design: We build with deep respect for our end users, listening closely to their feedback and needs.

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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.