Lead Solution Architect
22 hours ago
Role: Lead Solution Architect (AI Infrastructure, Kubernetes & HPC)
Location: Bangalore/Pune
Duration: Full Time
"Just a heads-up — the second round will need to be attended in person, as per the client's request."
Role Type: Senior Role - Delivery-focused infrastructure role (non–presales; may include limited presales engagement)
Core Focus Areas
Kubernetes Platforms:
Proficiency in container orchestration platforms, especially Red Hat OpenShift, SUSE Rancher, and CNCF Kubernetes.
Experience with GPU-accelerated workloads and tools like NVIDIA GPU Operator and DCGM
Proven ability to integrate Kubernetes with AI/ML workloads and GPU infrastructure in hybrid or private cloud environments.
HPC Experience:
Experience architecting HPC clusters, including GPU/compute nodes and HPC storage technologies (e.g., Lustre, WEKA, Parallel Filesystems).
Understanding of high-speed networking (e.g., InfiniBand, Mellanox, RoCE)
Experience with HPC cluster management tools such as HPE Cluster Management (HPCM) or NVIDIA Base Command Manager.
Familiarity with HPC workload schedulers like Slurm or Altair PBS Pro.
Infra & Hardware Stack:
Strong background in Linux system administration (RHEL / SLES /Ubuntu) and virtualization (KVM or OpenShift Virtualization).
Primary focus on HPE servers and storage; experience with Dell, Lenovo, Supermicro, NVIDIA DGX/HGX platforms is acceptable.
Solid understanding of compute, storage, and networking fundamentals in enterprise environments.
AI Platform Enablement:
Experience deploying and supporting NVIDIA AI Enterprise and related AI/ML frameworks.
Familiarity with DevOps/MLOps practices, including CI/CD, Infrastructure as Code (IaC), and cloud-native security.
Project Delivery:
Demonstrated success in infrastructure project delivery, including platform build-outs for AI/ML and HPC workloads.
Ability to collaborate with cross-functional teams and align technical solutions with business goals.
Trainability Clause
Candidates with strong Kubernetes or HPC and AI/ML experience but limited infrastructure hardware exposure may be considered if they demonstrate trainability in server and platform environments.
Delivery Scope
This is a delivery-focused role with limited presales involvement.
The architect will be responsible for designing and building platforms, especially HPE Private Cloud AI and HPE AI Factory solutions, to support enterprise-grade AI workloads.
Instructions & Findings
HPC experience is strongly preferred; however, candidates without direct HPC exposure may be considered if they demonstrate strong alignment with other key requirements (Strong Linux, Network & Storage skills) and a clear aptitude for learning HPC technologies.
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