Principal Solutions Architect

Rafay; United States; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Rafay seeks a Principal Solutions Architect to enable enterprise customers deploying and scaling AI/ML workloads on Rafay’s GPU Platform-as-a-Service. The role combines hybrid leadership with hands-on architecture, building a team of Solutions Architects across platform engineering, MLOps, data science, and infrastructure.

You will design production-ready AI infrastructure on Kubernetes and GPU ecosystems, mentor engineers, and partner with sales and executives to drive scalable customer success.

Qualifications

• 10+ years in infrastructure, platform, or solutions engineering roles.
• 3+ years focused on AI/ML infrastructure or MLOps.
• 2+ years direct people management, hiring and performance reviews.
• Demonstrated ability to lead and grow a technical team while remaining hands-on with customers.
• Deep Kubernetes expertise including cluster lifecycle and RBAC.
• Hands-on experience with NVIDIA GPU infrastructure (H100/H200/B200).
• Proficiency with distributed training concepts (NCCL, tensor parallelism).
• Experience with LLM inference serving and optimization.
• Familiarity with GPU Operator, MIG, SR-IOV, and network fabrics.
• Strong scripting and automation skills (Python, Bash, Go).
• Ability to explain complex concepts to diverse audiences and exec stakeholders.
• Experience with AWS, Azure, or GCP platforms.
• Familiarity with monitoring tools like Prometheus, Grafana, and OpenTelemetry.
• Understanding of GPU-based workloads and model serving.
• Proven troubleshooting capabilities for infra issues.

Responsibilities

• Recruit, hire, and onboard Solutions Architects as the team scales.
• Directly manage a team of Solutions Architects with coaching and support.
• Set goals; conduct 1:1s and performance reviews.
• Own career development planning for direct reports and succession planning.
• Foster an inclusive, high-performing team culture aligned with Rafay’s values.
• Manage team capacity, prioritization, and staffing against demand.
• Partner with sales, engineering, and executives on hiring plans.
• Mentor and upskill both direct reports and junior staff.
• Design AI/ML platform architectures for inference, training, data pipelines.
• Develop reference architectures for GPU clusters and LLM serving infra.
• Evaluate inference serving frameworks (vLLM, TGI, Triton).
• Advise on GPU fabric topology for distributed training.
• Design observability strategies using DCGM, OpenTelemetry, and eBPF.
• Translate infra requirements into actionable platform designs.
• Deliver technical presentations, workshops, and PoCs.
• Serve as trusted advisor on AI infra strategy, costs and scaling.
• Partner with customer stakeholders to understand workload requirements.
• Architect networking, identity, observability, and security integrations.
• Monitor and troubleshoot production GPU workloads and cluster health.
• Lead root cause analysis for complex customer issues.
• Document reference architectures and best practices.

Skills

10+ years infra/platform/solutions eng

AI/ML infra or MLOps

People management

Leadership with hands-on approach

Kubernetes RBAC and lifecycle

NVIDIA GPU infra (H100/H200/B200)

Distributed training (NCCL)

LLM inference serving

GPU Operator/MIG/SR-IOV

Scripting: Python/Bash/Go

Communication of complex tech

Cloud platforms AWS/Azure/GCP

Monitoring: Prometheus/Grafana/OpenTel

GPU workloads/model serving

Troubleshooting infra

Customer-facing collaboration

Job description

Rafay seeks a Principal Solutions Architect to enable enterprise customers/Neo clouds in deploying, operating, and scaling AI/ML workloads on our GPU Platform-as-a-Service offering. This is a hybrid technical leadership and people-management role: alongside hands-on, customer-facing architecture work, this person will build, lead, and grow a team of Solutions Architects, collaborating with platform engineering, MLOps, data science, and infrastructure teams to architect production-ready AI infrastructure solutions built on Kubernetes and GPU-accelerated environments.

Key Responsibilities

• Recruit, hire, and onboard Solutions Architects as the team scales
• Directly manage a team of Solutions Architects, including workload allocation, coaching, and day-to-day support
• Set individual and team goals; conduct regular 1:1s and performance reviews
• Own career development planning for direct reports, including skills growth, promotion readiness, and succession planning
• Foster an inclusive, high-performing team culture aligned with Rafay's values
• Manage team capacity, prioritization, and staffing against customer and project demand
• Partner with sales, engineering, and executive leadership on hiring plans and team structure
• Mentor and upskill both direct reports and junior team members across the broader organization

Technical & Customer-Facing Responsibilities

• Design comprehensive AI/ML platform architectures covering inference, training, and data pipelines
• Develop reference architectures for GPU cluster deployment and LLM serving infrastructure
• Evaluate inference serving frameworks including vLLM, TGI, and Triton
• Advise on GPU fabric topology options for distributed training scenarios
• Design observability strategies using DCGM, OpenTelemetry, and eBPF
• Translate infrastructure requirements into actionable platform designs
• Deliver technical presentations, workshops, and proof-of-concept engagements
• Serve as trusted advisor on AI infrastructure strategy, cost optimization, and scaling
• Partner with customer stakeholders to understand workload requirements
• Architect networking, identity management, observability, and security integrations
• Monitor and troubleshoot production environments for GPU utilization and cluster health
• Lead root cause analysis for complex customer issues
• Document reference architectures and implementation best practices

Required Qualifications

• 10+ years in infrastructure, platform, or solutions engineering roles
• 3+ years focused on AI/ML infrastructure or MLOps
• 2+ years of direct people-management experience, including hiring, performance management, and career development of technical staff
• Demonstrated ability to lead and grow a technical team while remaining hands-on with customers and architecture
• Deep Kubernetes expertise including cluster lifecycle and RBAC
• Hands-on experience with NVIDIA GPU infrastructure (H100/H200/B200 preferred)
• Proficiency with distributed training concepts (NCCL, tensor parallelism)
• Experience with LLM inference serving and optimization
• Familiarity with GPU Operator, MIG, SR-IOV, and network fabrics
• Strong scripting and automation skills (Python, Bash, Go preferred)
• Ability to communicate complex technical concepts to diverse audiences, including executive stakeholders
• Experience with AWS, Azure, or GCP platforms
• Familiarity with monitoring tools like Prometheus, Grafana, and OpenTelemetry
• Understanding of GPU-based workloads and model serving
• Proven troubleshooting capabilities for infrastructure issues
• Excellent communication, coaching, and customer-facing skills

Preferred Qualifications

• Experience building a Solutions Architecture or technical pre-sales team from the ground up
• Formal people-management training or leadership certification
• Enterprise customer support experience in cloud-native environments
• Familiarity with PyTorch and TensorFlow frameworks
• Experience with Run:AI and Slurm
• GPU scheduling and autoscaling expertise
• Multi-tenant Kubernetes environment knowledge
• MLOps platform experience
• Technical workshop leadership experience
• Relevant certifications (CKA, CKAD, AWS/Azure/GCP Solutions Architect)
• Understanding of multi-tenant GPU isolation technologies

Why Join Rafay?

Rafay is at the forefront of GPU PaaS technologies and Kubernetes and we offer unique opportunities to join a winning team working on foundational technology for cloud and AI/ML services and enterprises. We work in a collaborative environment that rewards creative thinking and provides opportunities to advance professional careers in advanced technology development. On top of this we offer a fun and dynamic work environment, a competitive salary, robust benefits and attractive stock options. As the first of our kind, we are truly in a class of our own.