Staff Solutions Engineer – Edge AI & Infrastructure

About the role

Qualcomm is looking for a Staff Solutions Engineer to drive edge AI and infrastructure initiatives across the UAE. The role spans the full lifecycle from pre‑sales solutioning to post‑sales technical success, ensuring customer opportunities become shippable, scalable solutions.

Key responsibilities

• Lead discovery workshops with customers and internal stakeholders to capture requirements, define success criteria, and shape solution scopes.
• Create solution blueprints that integrate edge compute, AI workloads, and connectivity, including feasibility assessments and platform fit recommendations.
• Develop and maintain reusable technical assets such as reference architectures, demo scripts, BOM guidance, and integration patterns.
• Partner with engineering and product teams to translate customer needs into actionable technical requirements and provide structured field feedback.
• Support sales by leading technical engagements, architecture reviews, workshops, competitive positioning, and stakeholder presentations.
• Own technical deliverables for customer‑facing proposals, solution documents, and demo/PoC execution.
• Drive post‑sales success through demos, pilots, and scaled rollouts of edge AI devices and infrastructure solutions.

Required profile

• Strong expertise in AI model development, quantization, performance optimization, and deployment.
• Ability to define system architecture, size workloads, and design end‑to‑end edge solutions.
• Experience building deep‑learning models across diverse hardware platforms.
• Self‑starter who can operate independently, lead technical execution, and act as a trusted partner to sales and engineering teams.
• Excellent cross‑functional collaboration skills.

Required skills

• AI models and model quantization
• Performance optimization for edge workloads
• Deep learning frameworks (TensorFlow, PyTorch)
• Programming (Python, C/C++)
• Linux operating system
• Container orchestration tools (Docker, Kubernetes)
• Edge compute platforms and connectivity technologies