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 - 8+ 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.

📌 Principal Solutions Architect (Colombia)
🏢 Rafay Systems
📍 Colombia