Senior Solutions Engineer: AI/ML GPU on Kubernetes

Rafay

United States

On-site

USD 140,000 - 180,000

Full time

12 days ago

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Benefits offered by this job

Competitive salary

Robust benefits

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Job summary

Rafay seeks a Senior Solutions Engineer to partner with enterprise customers, architect and deploy cloud-native Rafay platform solutions, and optimize GPU-enabled Kubernetes environments. You will lead technical engagements, design multi-cloud deployments, and mentor junior engineers while ensuring SLAs and customer success.

Ideal candidates bring 8+ years in customer-facing roles, hands-on AI/ML workflows, and strong Kubernetes/cloud-native expertise.

Qualifications

8+ years in customer-facing technical roles with implementation or consulting experience.
Hands-on AI/ML model inference and deployment workflows.
Experience with NVIDIA GPU infrastructure (H100/H200) preferred.
Familiar with GPU Operator, MIG, SR-IOV, and GPU networking basics.
Knowledge of LLM inference stacks (vLLM/Triton).
Strong Kubernetes and cloud-native expertise.
Excellent written and verbal communication; able to lead projects.

Responsibilities

Serve as the primary technical lead for customer implementation engagements.
Collaborate with customers on requirements, architecture reviews, and solution design.
Design Rafay platform capabilities across public, private, and hybrid clouds.
Troubleshoot complex infrastructure, Kubernetes, and virtualization issues.
Create technical docs, runbooks, and implementation guides.
Mentor junior engineers and drive process improvements.
Stay current on Rafay features and industry trends.