Presales Engineer İş İlanı

Pre-Sales Engineer — GPU & AI Infrastructure NVIDIA GPUs | Red Hat OpenShift | Kubernetes | Rafay We are looking for a hands-on Pre-Sales Engineer who can help customers evaluate, design, and adopt GPU infrastructure for AI/ML workloads. You will work alongside our sales team, lead technical discussions, and build working Proofs of Concept (POCs) and customer pilots. This role combines customer-facing consulting with practical infrastructure engineering. Working model: Hybrid, with flexible working hours Experience: 3+ years in pre-sales engineering, solution consulting, or technical consulting Languages: Fluent English required; Turkish is an advantage Is This Role Right for You? You could be a strong match if you can: Independently build and troubleshoot Kubernetes and Red Hat OpenShift environments. Deploy containerized AI/ML workloads on NVIDIA GPUs. Turn customer requirements into a working POC with clear success criteria. Explain architecture, technical trade-offs, and business value to both engineers and decision-makers. Direct Rafay experience is preferred. We also welcome candidates with strong experience using comparable Kubernetes management or GPU infrastructure platforms. What You Will Do Lead technical discovery sessions to understand customer workloads, infrastructure, security requirements, and business objectives. Design and deliver hands-on POCs and customer pilots using Rafay, Kubernetes, OpenShift, and NVIDIA GPU technologies. Demonstrate GPU provisioning, workload deployment, and GPU sharing, including NVIDIA Multi-Instance GPU (MIG) and time-slicing where appropriate. Design solutions covering cluster architecture, networking, storage, tenant access, resource quotas, and multi-cluster management. Deploy and troubleshoot NVIDIA GPU Operator and its supporting software components. Deliver product demonstrations, technical workshops, and architecture presentations. Define POC acceptance criteria and measure outcomes such as GPU utilization, workload throughput, latency, and resource consumption. Prepare technical proposals, RFP responses, architecture diagrams, and implementation documentation. Document pilot results, support customer handovers, and share feedback with product and engineering teams. What You Need to Bring Relevant experience At least 3 years of experience in pre-sales engineering, solution consulting, or technical consulting within cloud, platform infrastructure, or AI/ML environments. Demonstrated experience delivering customer-facing POCs or pilots involving GPU-enabled workloads. A bachelor’s degree in computer science, Engineering, or a related discipline, or equivalent practical experience. Hands-on technical skills Kubernetes and OpenShift: Cluster administration, workload scheduling, networking, persistent storage, RBAC, Operators, and troubleshooting. NVIDIA GPU infrastructure: GPU Operator deployment, GPU drivers, container runtime integration, and compatibility troubleshooting. GPU sharing: Practical experience with MIG or time-slicing, and an understanding of their capacity, performance, and isolation trade-offs. AI/ML workloads: Experience deploying and supporting containerized training or inference workloads. Linux and automation: Confidence working with Linux, Git, YAML, Helm, and Bash or Python. Platform architecture: Understanding of multi-tenancy, resource quotas, access controls, and multi-cluster management. Customer-facing skills Ability to translate customers’ needs into a technical solution and a structured POC plan. Clear presentation, technical writing, and troubleshooting skills. Ability to explain technical decisions and business value to different audiences. Fluent spoken and written English. What Will Help You Stand Out You do not need every item below to apply: Hands-on experience with Rafay GPU PaaS or comparable platforms. Experience configuring self-service GPU provisioning and tenant environments. Experience with Terraform, Ansible, or GitOps workflows. Familiarity with NVIDIA DCGM, Prometheus, and Grafana. Experience with inference-serving tools such as NVIDIA Triton Inference Server or vLLM. Understanding of GPU sizing, capacity planning, and infrastructure cost optimization. Experience supporting enterprise RFPs and technical evaluations. Turkish language proficiency. Relevant certifications are highly preferred, but equivalent hands-on expertise is welcome: Certified Kubernetes Administrator ( CKA ). Red Hat OpenShift administration certification ( EX280 ). NVIDIA-Certified Professional: AI Infrastructure ( NCP-AII ) or AI Operations ( NCP-AIO ). Certified Kubernetes Security Specialist ( CKS ) as an additional advantage.

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. A global, inclusive, and collaborative company culture. Hands-on work with GPU computing, AI/ML infrastructure, Kubernetes, OpenShift, and the NVIDIA ecosystem. How to Apply Submit your CV or résumé in English , along with a short description of one relevant GPU, Kubernetes, or OpenShift project. Please briefly explain: The customer requirement or technical challenge. Your personal contribution and the technologies you used. The outcome or measurable result. Include any relevant certifications. Please avoid sharing confidential customer information. If you meet the core requirements but do not have every preferred skill or certification, we encourage you to apply.