6 часов назад
Production Engineer (AI Infrastructure)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Production Engineer (AI Infrastructure): Building and scaling Kubernetes tooling and managed VM platforms for external customers with an accent on infrastructure reliability, observability, and automation. Focus on incident response, root cause analysis, proactive remediation, and maintaining high SLIs and SLOs across distributed AI infrastructure.
Location: Dublin, Ireland — on-site
Company
builds vertically integrated AI infrastructure spanning energy, data centers, and cloud services for demanding AI workloads.
What you will do
- Build and scale tooling and features for managed Kubernetes and managed virtual machine platforms.
- Monitor system alerts, performance metrics, and logs while improving monitoring and alerting capabilities.
- Respond to incidents, conduct post-mortems and root cause analyses, and prevent recurring issues through automation.
- Maintain high service level indicators and objectives across distributed infrastructure.
- Collaborate with software engineers on resilient code, review changes, and support data center deployments and retrofits.
- Document technical work and share operational knowledge with the team.
Requirements
- 3–6 years of professional Production Engineering experience.
- Experience building Kubernetes platforms or Kubernetes controllers.
- Understanding of distributed systems, reliability, scaling, and infrastructure design trade-offs.
- Proficiency in Python, Go, or a similar programming language.
- Experience with Unix/Linux environments, observability tooling, logging, monitoring, and alerting.
- Knowledge of server-class hardware and provisioning, TCP/IP networking, RPC serving designs, and basic information security practices.
Culture & Benefits
- Full-time employment in a customer-focused Production Engineering team.
- Pension contributions and private health and dental insurance.
- Income protection and life assurance.
- Competitive compensation determined by education, experience, skills, internal equity, and market data.
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