Pre‑Sales Engineer – GPU & AI Infrastructure

About the role

We are looking for a hands‑on Pre‑Sales Engineer to help customers evaluate, design, and adopt GPU infrastructure for AI/ML workloads. You will work alongside the sales team, lead technical discussions, and build working Proofs of Concept (POCs) and customer pilots.

Key responsibilities

• Lead technical discovery sessions to understand customer workloads, infrastructure, security requirements, and business objectives.
• Design and deliver hands‑on POCs and pilots using Rafay, Kubernetes, OpenShift, and NVIDIA GPU technologies.
• Demonstrate GPU provisioning, workload deployment, and GPU sharing (including MIG and time‑slicing).
• Design solutions covering cluster architecture, networking, storage, tenant access, resource quotas, and multi‑cluster management.
• Deploy and troubleshoot NVIDIA GPU Operator and supporting software components.
• Deliver product demos, technical workshops, and architecture presentations.

Required profile

• At least 3 years of experience in pre‑sales engineering, solution consulting, or technical consulting within cloud, platform infrastructure, or AI/ML environments.
• Bachelor’s degree in Computer Science, Engineering, or related discipline, or equivalent practical experience.
• Fluent spoken and written English; Turkish is a plus.

Required skills

• Kubernetes and Red Hat OpenShift cluster administration, networking, storage, RBAC, Operators, and troubleshooting.
• NVIDIA GPU infrastructure: GPU Operator deployment, drivers, container runtime integration, MIG, and time‑slicing.
• Experience deploying containerised AI/ML training or inference workloads.
• Linux, Git, YAML, Helm, Bash or Python scripting.
• Familiarity with Terraform, Ansible, or GitOps workflows (preferred).
• Knowledge of NVIDIA DCGM, Prometheus, Grafana, and inference‑serving tools such as NVIDIA Triton (optional).

What we offer

• Competitive salary and performance‑based bonus.
• Flexible working hours and a hybrid working model.
• Career development opportunities across solution architecture, customer success, and product development.
• Global, inclusive, and collaborative company culture.
• Hands‑on work with GPU computing, AI/ML infrastructure, Kubernetes, OpenShift, and the NVIDIA ecosystem.