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Kyndryl

Managed IT infrastructure and cloud services

Technical SME 3 - AI Compute

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-timeJakarta, IndonesiaNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's degree in Computer Science, Information Technology, Computer Engineering, Electrical Engineering, or a related technical discipline.
  • At least 8 years of experience supporting AI infrastructure, high-performance computing, large-scale Linux environments, cloud platforms, or enterprise infrastructure engineering.
  • Deep expertise in Linux systems administration, troubleshooting, performance tuning, and production operations.
  • Strong knowledge of NVIDIA data center GPUs and large-scale GPU computing environments.
  • Hands-on experience with GPU diagnostics, GPU health monitoring, XID analysis, ECC error investigation, and hardware troubleshooting.
  • Strong understanding of PCIe architecture, NVLink, NVSwitch, GPU interconnect technologies, and firmware-to-driver compatibility relationships.
  • Experience supporting AI workload orchestration platforms such as Kubernetes, Slurm, or similar cluster management technologies.
  • Experience performing advanced root cause analysis across hardware, firmware, operating systems, networking, storage, and platform services.
  • Strong knowledge of firmware lifecycle management, BIOS, BMC, Redfish, IPMI, driver management, and platform maintenance processes.
  • Experience managing major incidents, technical escalations, change management activities, and OEM/vendor engagement.
  • Ability to assess platform performance, capacity utilization, scalability, and operational risks.
  • Excellent verbal and written communication skills in English.

Responsibilities

  • Act as the highest level of technical escalation for complex AI compute platform incidents involving GPUs, Linux systems, storage, networking, and distributed AI workloads.
  • Lead advanced fault isolation and troubleshooting across GPU, CPU, memory, PCIe, NVLink, NVSwitch, firmware, BMC, operating system, and platform infrastructure layers.
  • Perform deep analysis of GPU health, XID events, ECC errors, performance degradation, system instability, and hardware-related failures.
  • Lead technical root cause analysis and problem management investigations, and define permanent corrective actions that improve platform reliability and resilience.
  • Drive platform lifecycle management activities, including firmware validation, compatibility assessments, maintenance planning, change risk evaluations, and rollback strategies.
  • Automate operational tasks, diagnostics, monitoring, and remediation workflows using scripting and infrastructure automation tools.
  • Analyze capacity, utilization, performance, availability, latency, and service-level objectives across AI infrastructure environments, and recommend optimization opportunities.
  • Collaborate with OEMs, technology partners, and internal engineering teams to resolve complex technical issues and support large-scale AI platform deployments.

Desired Qualifications

  • Experience supporting AI, GenAI, machine learning, GPU cloud, or large-scale HPC environments.
  • Expertise with Python, Ansible, Bash, or similar automation and infrastructure-as-code technologies.
  • Experience with Site Reliability Engineering principles, service-level objectives, observability, and operational excellence practices.
  • Experience supporting NVIDIA AI platforms, DGX systems, HGX platforms, or large multi-GPU environments.
  • Knowledge of liquid-cooled and high-density AI infrastructure platforms.
  • Experience with DCGM, NVIDIA-SMI, GPU telemetry, performance profiling, and infrastructure monitoring tools.
  • Familiarity with storage and networking technologies supporting AI workloads, including InfiniBand, RDMA, high-performance storage, and distributed file systems.
  • Experience leading OEM escalations and working with NVIDIA, server vendors, and infrastructure partners to resolve complex platform issues.
  • Experience defining operational standards, diagnostic frameworks, health baselines, runbooks, and platform acceptance criteria.
  • Mandarin language proficiency for senior-level technical engagement and collaboration with regional stakeholders and technology partners.

About the Company

Kyndryl

Managed IT infrastructure and cloud services

Kyndryl provides managed IT infrastructure services for large enterprises, helping them run and modernize their technology environments. Its offerings cover cloud adoption, cybersecurity, security operations, and digital workplace services, all delivered under long-term managed-service contracts. The company works by partnering with major technology providers (including Microsoft) to offer integrated, end-to-end solutions, often complemented by a new security operations center (SOC) and other security capabilities. This focus sets it apart from competitors through scale, enterprise-grade governance, and a history rooted in IBM’s infrastructure services, now independent but aligned with large technology partners. The goal is to support digital transformation by providing reliable, scalable, and secure infrastructure management that enables enterprises to operate efficiently and securely in a cloud-enabled world.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
2021

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