Senior Solutions / Pre-Sales Engineer – AI Platforms

Role overview

Core responsibilities

• Own technical pre-sales from early discovery through solution definition, proposal, demonstration, validation, and delivery handover.
• Lead discovery and translate customer business, workload, data, model, security, and operational requirements into practical solutions.
• Design and size GPU infrastructure and architectures across compute, networking, storage, Kubernetes, orchestration, model serving, training, and fine-tuning.
• Support AI platform service offerings and architect high-speed networking and AI-optimized storage solutions.
• Demonstrate and customize the platform, technical walkthroughs, and proof-of-value scenarios for customer use cases.
• Advise on agents, RAG, model adaptation, evaluation, guardrails, and enterprise integration.
• Create proposals, sizing models, BOMs/BoQs, diagrams, service definitions, assumptions, and handover material.
• Contribute to RFP/RFI/tender responses, customer presentations, opportunity shaping, vendor validation, and reusable pre-sales assets.
• Travel to customer sites across the UAE for workshops, demonstrations, technical validation, proof-of-value work, and executive discussions.

Required qualifications

• 7–10 years in pre-sales/solutions engineering, AI platform or MLOps architecture, infrastructure/systems engineering, or a similar customer-facing technical role.
• Strong hands-on background across AI platforms, MLOps, Kubernetes, compute, networking, storage, virtualization, and data centers.
• Experience with discovery, solution sizing, proposals, BOM/BoQ creation, RFP/RFI responses, demonstrations, and technical handover.
• Practical Kubernetes knowledge spanning production cluster resources, security, scheduling, quotas, access control, and observability.
• Understanding of GPU orchestration, resource scheduling, multi-tenancy, workload isolation, and capacity planning.
• Ability to design and size across platform, compute, storage, and networking and to work independently in complex sales cycles.
• Strong communication, commercial awareness, technical documentation, and customer-facing skills.

Preferred qualifications

• Enterprise, government, regulated, or sovereign AI experience is preferred.
• GPU infrastructure, GPU scheduling, model serving, high-speed networking, enterprise storage, or secure and air-gapped deployment experience is preferred.
• AI-agent, copilot, RAG, agentic workflow, document intelligence, or AI automation experience is preferred.
• Arabic language ability is advantageous but not required.

First 90-day success