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radar
Страна
США
Зарплата
130 000 $ – 180 000 $
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SeniorГибридПолная занятость

Senior DevOps Engineer

Оценка ИИ

Отличная вакансия в быстрорастущем стартапе с серьезным финансированием ($104M+). Предлагается работа с передовым стеком технологий и реальное влияние на продукт, а также конкурентная зарплата и расширенный пакет льгот.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью работать на стыке облачных технологий, IoT и встраиваемых систем (Yocto, Xilinx), а также строгими требованиями к безопасности SOC 2. Роль требует глубоких знаний не только в стандартном DevOps-стеке, но и в ML Ops и системном администрировании Linux.

Анализ зарплаты

Медиана165 000 $
Рынок140 000 $ – 195 000 $
Оценка ИИ

Предлагаемая зарплата ($130k - $180k) полностью соответствует рыночным стандартам для Senior DevOps ролей в Сиэтле, где медиана составляет около $165k. Верхняя граница диапазона привлекательна даже для опытных специалистов.

Сопроводительное письмо

I am writing to express my strong interest in the Senior DevOps Engineer position at RADAR. With over 5 years of experience in managing complex cloud and edge infrastructures, I am particularly drawn to your mission of transforming physical retail through RFID and AI. My background in scaling Kubernetes environments and implementing robust CI/CD pipelines using GitHub Actions and Argo CD aligns perfectly with your current technical roadmap.

In my previous roles, I have successfully migrated legacy workloads to Kubernetes and optimized cloud costs, which are key objectives for your first 90 days. I am also experienced in Terraform for IaC and have a deep understanding of SOC 2 compliance requirements. The opportunity to work on a diverse technical landscape that includes IoT, embedded systems, and ML Ops is incredibly exciting, and I am confident that my skills in Linux debugging and distributed systems will be an asset to your Seattle-based team.

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Составьте идеальное письмо к вакансии с ИИ-агентом

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Откликнитесь в radar уже сейчас

Присоединяйтесь к RADAR, чтобы внедрять инновации в ритейле и управлять сложной инфраструктурой на стыке Cloud, IoT и ML!

Описание вакансии

ABOUT US

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!

OUR VALUES

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.

ABOUT THE JOB

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.

Responsibilities:

  • 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.

ABOUT YOU

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.

+400% к собеседованиям

Создайте идеальное резюме с помощью ИИ-агента

Создайте идеальное резюме с помощью ИИ-агента

Навыки

  • Kubernetes
  • Terraform
  • GitHub Actions
  • Argo CD
  • Go
  • Python
  • Java
  • C++
  • Gradle
  • Linux
  • IoT
  • ML Ops
  • Yocto
  • Xilinx
  • SOC 2

Возможные вопросы на собеседовании

Вакансия предполагает миграцию с Cloud Run на Kubernetes в первые 90 дней. Важно понять опыт кандидата в таких переходах.

Расскажите о вашем опыте миграции сервисов из Serverless-решений (например, Cloud Run) в Kubernetes: с какими основными трудностями вы сталкивались?

Компания работает с IoT и встраиваемыми системами. Это специфическая область для DevOps.

Как бы вы организовали CI/CD пайплайн для прошивок и встраиваемого ПО, учитывая использование Yocto и необходимость тестирования на реальном оборудовании?

Упоминается необходимость соблюдения SOC 2. Это критично для финтех и ритейл-платформ.

Какие конкретные практики в CI/CD и управлении инфраструктурой (IaC) вы внедряли для обеспечения соответствия требованиям SOC 2?

Одной из задач является внедрение эфемерных сред разработки.

Какой подход вы выберете для реализации эфемерных (временных) окружений для разработчиков в среде Kubernetes?

Вакансия включает задачи по ML Ops.

Каков ваш опыт автоматизации жизненного цикла моделей машинного обучения и их деплоя на Edge-устройства?

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radar
Страна
США
Зарплата
130 000 $ – 180 000 $