Solutions Architect - NCP DevOps

Maintaining large scale computational and AI infrastructure, focusing on monitoring, logging, workload orchestration (Kubernetes and Linux job schedulers).

Optimize scalable, production-ready Kubernetes-based container platforms coordinated with enterprise-grade networking and storage.

Serve as a key technical resource, develop, refine, and document standard methodologies and operational guidelines to be shared with internal teams.

Lead technical engagements, helping customers troubleshoot, resolve complex issues, and advocate for their technical needs.

Support Enterprise, Research & Development activities and engage in POCs/POVs to validate new features, architectures, and upgrade approaches.

Partner with APAC Regional and HQ Engineering, Product and Sales teams to develop, plan best suitable solutions for Partners. Enable development and growth of product features through customer feedback and proof-of-concept evaluations

Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.

Create and deliver high-quality documentation, including runbooks, onboarding materials, and best-practice guides for customers and internal teams.

Become the technical leader for assigned customer accounts, providing strategic guidance on DevOps and platform architecture and influencing long-term infrastructure and operations decisions.

Education & Experience: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, with 5+ years of professional experience in managing scalable cloud environments and automation engineering roles.

Proven Hardware & Software knowledge and experience at scale: Familiarity with HPC and AI technologies (CPUs, GPUs, high-speed interconnects) and supporting software stacks.

Cloud & HPC Expertise: Proven understanding of networking fundamentals (TCP/IP stack), data center architectures (from storage to Network, GPU accelerated compute and of course DevOps software stacks, as well as hands-on experience managing HPC/AI clusters, including deployment, optimization, and fixing issues.

Kubernetes & AI/ML Workloads: Extensive experience with Kubernetes for container orchestration, resource scheduling, scaling, and integration with HPC environments.

Linux & Storage Systems: Deep knowledge of Linux (RedHat/CentOS, Ubuntu), OS-level security, and protocols (TCP, DHCP, DNS). Experience with storage solutions such as Lustre, GPFS, ZFS, XFS, and emerging Kubernetes storage technologies.

Automation & Observability: Proficiency in Python and Bash scripting, configuration management, and Infrastructure-as-Code tools (e.g., Ansible, Terraform). Experience with observability stacks (Grafana, Loki, Prometheus) for monitoring, logging, and building fault-tolerant systems.

Solution Architecture & Customer Engagement: Strong background in crafting scalable solutions and providing consultative support to customers.

Experience with GPU-focused hardware and software (e.g., NVIDIA DGX, CUDA, GPU Operator).

Solid hands-on knowledge of Kubernetes and container-based microservices architectures.

Skills in large-scale computing and cluster computing, data center design include high speed interconnect with Spectrum/InfiniBand, Cluster Storage and Scheduling related design and/or management experience.

Knowledge of CI/CD pipelines for software deployment and automation.

Background with RDMA-based fabrics (InfiniBand or RoCE) in HPC or AI environments.

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