AI Infrastructure / Platform Engineer

Data lowongan bersumber dari dealls. Tombol “Lamar” mengarahkan Anda ke halaman aslinya.

Performance Optimization

Conduct load and performance testing, assess platform capacity, and improve system reliability, application responsiveness, and GPU utilization within data centre power and cooling constraints.

Troubleshooting & Incident Management

Diagnose and resolve issues across hardware, operating systems, storage, networks, and applications. Identify root causes, document solutions, and maintain clear operational procedures.

Client Onboarding & Technical Support

Support client onboarding, access provisioning, API key management, data separation, and usage limits. Act as a technical point of contact, provide technical consultations and usage reports, and help resolve incidents in line with agreed service levels.

Security & Infrastructure Operations

Maintain access controls, logging, encryption, backups, and security documentation. Coordinate with hardware vendors and data centre providers on maintenance, repairs, warranties, and infrastructure requirements.

Kualifikasi

• [Main Requirements]
• Are enthusiastic and passionate about
• computer hardware
• , particularly GPUs, CPUs, and server infrastructure.
• Understand how to install, configure, and run software on physical hardware, from operating systems and system services to applications.
• Have experience
• managing
• Linux servers in production
• , with a solid understanding of SSH, storage, networking, and security hardening.

Have hands-on experience with GPU servers, including drivers, CUDA, and troubleshooting. Experience with AI workloads or large language model deployment is a plus.

• Understand the fundamentals of
• networking, connectivity, firewalls, and network security.
• Are familiar with containers and scripting using Bash or Python.
• Can build or maintain monitoring and alerting systems, such as Prometheus and Grafana, and understand how to identify meaningful metrics.
• Enjoy troubleshooting issues across hardware, operating systems, networks, and applications using logs, metrics, and system tools.
• Use innovative tools, including AI tools, to work efficiently while carefully reviewing and validating their output before production use.
• Have strong
• client-facing and service-oriented skills
• , with the ability to support onboarding, prepare technical reports, explain technical issues, and provide practical consultations.
• Communicate clearly, collaborate effectively, and take ownership of technical responsibilities in a dynamic environment.
• [Nice to Have]
• Experience with multi-GPU servers, GPU interconnects, or AI inference engines such as vLLM.
• Familiarity with Kubernetes and infrastructure-as-code tools such as Ansible or Terraform.
• Experience with monitoring and observability tools, high-speed networking (100 Gbps or above), or infrastructure performance testing.
• Knowledge of infrastructure security, data privacy, or compliance standards such as ISO 27001 and financial-sector regulations.