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DevOps Engineer, AI Platform
ГибридПолная занятостьDevOps & SREEnterprise Software
Join a global platform team building and operating distributed AI production systems. Own platform initiatives end to end, from design through implementation and production rollout, working with engineering, research, architecture, and product teams.
Обязанности
- Lead platform initiatives from design and implementation through production rollout
- Design, build, and operate highly available distributed systems on AWS and GCP
- Work across Kubernetes, Docker, Helm, CI/CD, automation, data, caching, and messaging layers
- Modernize and consolidate technology stacks into a coherent platform
- Build and operate infrastructure for AI workloads, including GPU inference platforms
- Improve system reliability, monitoring, and observability; troubleshoot issues across application, infrastructure, networking, operating system, and data layers
- Collaborate with platform, development, architecture, AI research, and product teams
Требования
- At least 2 years of experience in DevOps, platform, or SRE roles operating large-scale distributed production systems
- At least 2 years of experience with cloud inference services and NeoClouds
- At least 2 years of experience building and maintaining AI Factory systems using KubeFlow, Ray, or similar
- At least 2 years of experience with GPU inference technologies such as vLLM, SGLang, or NVIDIA Triton
- Hands-on expertise with AWS, GCP, or NeoClouds and infrastructure as code such as Terraform
- Strong Kubernetes and Helm expertise, including production operations and Kubernetes internals; experience with Docker and containerized systems
- Strong knowledge of networking and operating systems, including TCP/IP, DNS, load balancing, and Linux internals
- Experience with CI/CD automation, GitHub Actions, monitoring, and observability tools such as Prometheus and Grafana
- Proficiency with current AI coding tools and understanding of how to use them effectively
Будет плюсом
- Familiarity with AI evaluation and observability systems such as Opik, OpenEval, or LangSmith
Условия и преимущества
- Hybrid, flexible work environment
- Extended private health insurance, including mental health coverage
- Personal and professional development programs
- Occasional company-wide long weekends