Site Reliability Engineer - AI Infrastructure

Location: Singapore; regular travel and site assignments required, including extended periods away from home base

Company

hirify.global Technologies designs, builds, and operates energy-efficient AI infrastructure and the hirify.global AI Cloud GPU platform across Asia Pacific.

What you will do

• Deploy, configure, maintain, and commission high-end GPU servers, storage systems, networking equipment, and software in secure environments.
• Perform hardware diagnostics, system functionality checks, firmware updates, and firmware compliance troubleshooting.
• Support customer environments including bare-metal systems, HPC clusters, Kubernetes, and Slurm.
• Provide first-line engineering support for onsite hardware, network, and software incidents; escalate critical issues and document resolutions and lessons learned.
• Support the Global Operations Centre and collaborate with Field Service, HPC, Network Engineering, internal teams, stakeholders, and end users.
• Participate in an on-call rotation providing 24/7 responsiveness to critical issues.

Requirements

• Bachelor’s degree in computer engineering, computer science, or a related technical field.
• 5–8 years of experience in field service technical areas.
• Strong understanding of server hardware, firmware lifecycle, Linux environments, hardware troubleshooting, and physical and system-level security standards.
• Experience with scripting languages such as Bash and Python.
• Familiarity with configuration management, CI/CD tools, workload managers, cluster software such as Slurm, Kubernetes, and NVIDIA BCM, and observability tools such as Prometheus, Grafana, and ELK.
• Strong problem-solving, analytical, written, verbal communication, teamwork, and independent-working skills.
• Must be based in Singapore, available for regular travel and site assignments, and able to perform hands-on site duties and meet applicable travel and site access requirements.

Culture & Benefits

• Founder-led environment with accessible leaders, fast decisions, and minimal bureaucracy.
• Early ownership and direct contribution to a long-term, large-scale AI infrastructure roadmap.
• Exposure to AI infrastructure, energy systems, next-generation compute, and NVIDIA cloud and engineering partnerships.
• Work focused on sustainable AI infrastructure designed to operate as an asset to the energy grid.
• Support for professional growth across new domains and challenges beyond previous experience.