L3 Technical SME - AI Compute

Who We Are At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses.  We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. The Role Your Role At Kyndryl, we design, build, manage, and modernize the mission-critical technology systems that the world depends on every day. As an L3 Technical SME - AI Compute , you will serve as a senior technical authority for AI infrastructure platforms, providing deep expertise across GPU compute, Linux systems, AI cluster operations, platform reliability, and high-performance infrastructure environments. You will lead the resolution of complex technical challenges that extend beyond standard operational support, partnering with platform engineering, infrastructure, networking, storage, and OEM teams to maintain the reliability, scalability, and performance of mission-critical AI environments. This role combines deep GPU platform expertise with platform engineering, automation, performance optimization, and root cause analysis responsibilities. If you're passionate about solving the most complex AI infrastructure problems and influencing the future of large-scale GPU platforms, this is an opportunity to work on some of the industry's most advanced AI environments. What You'll Do 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 (RCA), 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 (SLOs) 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. Your Future at Kyndryl At Kyndryl, your growth is our priority. As an L3 AI Compute SME, you'll work at the forefront of AI infrastructure, helping customers and internal teams operate high-performance GPU environments that power next-generation AI, machine learning, and large language model workloads. You'll collaborate with industry-leading engineers, cloud providers, OEM partners, and technology innovators while expanding your expertise across AI platforms, platform engineering, automation, reliability engineering, and infrastructure architecture. Whether your career path leads toward Principal Engineering, AI Infrastructure Architecture, Platform Leadership, or Site Reliability Engineering, Kyndryl provides the opportunities and support to accelerate your growth. Who You Are You’re good at what you do and possess the required experience to prove it. However, equally as important, you have a growth mindset and are keen to drive your own personal and professional development. You are customer-focused, someone who prioritizes customer success in their work. And finally, you’re open and borderless, naturally inclusive in how you work with others.  Required Skills and Experience Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, Electrical Engineering, or a related technical discipline. Minimum 8+ years of experience supporting AI infrastructure, high-performance computing (HPC), 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 (RCA) 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. Strong analytical skills with the ability to assess platform performance, capacity utilization, scalability, and operational risks. Excellent verbal and written communication skills in English . Preferred Skills and Experience 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 (SRE) principles, service-level objectives (SLOs), 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 is advantageous for senior-level technical engagement and collaboration with regional stakeholders and technology partners. Being You The “Kyn” in Kyndryl means kinship, which represents the strong bonds we have with each other, our customers and our communities. We focus on ensuring all Kyndryls feel included and we welcome people of all cultures, backgrounds, and experiences. Even if you don’t meet every requirement, we encourage you to apply. We believe in growth, and we’re excited to see what you can bring. At Kyndryl, employee feedback has told us that our number one driver of employee engagement is belonging. That sense of belonging — being a valued, respected, trusted member of the team — is fundamental to our culture and fueling great experiences for our customers. This dedication to welcoming everyone into our company means that Kyndryl gives you the ability to thrive and contribute to our culture of empathy and shared success. That’s The Kyndryl Way. What You Can Expect Your career with us isn’t just a job—it’s an adventure with purpose.  We offer a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow.