11 часов назад
DevOps Engineer (AI)
85 000 - 180 000$
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
DevOps Engineer (AI/Kubernetes): Building and operating scalable infrastructure for AI agents and an enterprise software development platform with an accent on Kubernetes, CI/CD, Terraform, and observability. Focus on automating high-concurrency agent orchestration, improving deployment reliability, and designing secure, cost-efficient cloud environments.
Location: On-site at the Cambridge, Massachusetts headquarters
Salary: $85,000–$180,000 per year plus equity
Company
is an AI software development platform that autonomously converts enterprise requirements into production-ready software.
What you will do
- Build, manage, and scale Kubernetes clusters for AI agent workloads and production applications.
- Design and maintain CI/CD pipelines for application services and AI-driven workflows.
- Automate infrastructure provisioning, scaling, and operations with Python and Terraform.
- Deploy applications with Helm and maintain consistency across environments.
- Own monitoring, alerting, and distributed tracing for production services and APIs.
- Build reliable, high-throughput infrastructure for AI agent orchestration while improving developer experience, security, reliability, and cloud cost efficiency.
Requirements
- 5–8 years of DevOps or infrastructure engineering experience in production environments.
- Deep Kubernetes expertise, including deployment, scaling, networking, and troubleshooting.
- Strong Python skills for automation, scripting, and tooling.
- Hands-on experience with Helm, CI/CD pipelines, Terraform, and Infrastructure as Code.
- Experience with AWS, Azure, or GCP, plus strong Linux administration and Docker/containerization skills.
- Availability for on-site work at the Cambridge, Massachusetts headquarters.
Nice to have
- Certified Kubernetes Administrator (CKA) certification.
- Experience with MLOps tools such as MLflow or Kubeflow.
- Background in microservices architecture, service mesh technologies, API gateways, or advanced service mesh configurations.
Culture & Benefits
- In-person collaboration with an engineering team at the Cambridge headquarters.
- Autonomy to make architectural decisions for critical infrastructure.
- Work on AI infrastructure supporting enterprise and Fortune 500 customers.
- Company equity tied to performance.
- Focus on rapid execution, invention, customer value, high standards, and sustainable personal performance.
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