Customer Engineering, Field Engineer & Solutions Architect UAE

About the Role

We are seeking a Staff Solutions Engineer to support the execution of our edge initiatives by translating customer opportunities into shippable solutions—from solution definition to demo, pilot execution, and commercial deployment readiness. The role spans the full lifecycle: pre‑sales solutioning, sales enablement, and post‑sales technical success, with direct accountability for technical outcomes in demos, PoCs, pilots, and scaled rollouts across edge initiatives such as edge AI devices and edge infrastructure use cases.

• Lead discovery with internal stakeholders and end customers to capture requirements, define success criteria, and shape opportunities into a clear solution scope, architecture, and execution plan.
• Create solution blueprints that integrate edge compute, AI workloads, and connectivity, including feasibility assessments and fit‑to‑platform recommendations.
• Build and maintain reusable technical assets (reference architectures, demo scripts, BOM guidance, integration patterns) to accelerate field execution and repeatability.
• Partner with internal engineering/product teams to translate customer needs into actionable technical requirements, providing structured feedback based on field learnings.

• Support sales by leading technical engagements: architecture reviews, technical workshops, competitive positioning discussions, and stakeholder presentations.
• Own technical responses for customer‑facing deliverables (technical proposals, solution narratives, pilot plans) ensuring alignment with commercialization goals and operational requirements.
• Coordinate cross‑functional execution (BD, engineering, PMO, partners) to keep pilots and deal‑critical milestones on‑track and unblock dependencies.

• Design, build, and lead end‑to‑end demos and pilots, including environment setup, integration, performance validation, and customer walkthroughs.
• Own pilot execution governance: scope control, success criteria, issue triage, and closure readiness, driving toward a decision point for scale.
• Enable customer and partner teams via structured technical training and practical handover artifacts.

• Support transition from pilot to production by defining deployment prerequisites (security, monitoring, lifecycle ops, integration hardening) and ensuring production‑ready technical acceptance.
• Act as the technical escalation point during early deployments, driving issue resolution across internal teams and partners, maintaining customer confidence through clear communication.
• Establish repeatable rollout playbooks (deployment patterns, validation checklists, operational handover templates) to support scale across multiple opportunities.

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
• 10+ years in customer‑facing engineering, solutions engineering, field applications, systems engineering, or technical BD roles spanning the full cycle (discovery → PoC/pilot → deployment/scale).
• Proven ability to build and support AI embedded/edge deployments, with ecosystem integration experience across customer engineering, internal business units, and partners.
• Hands‑on experience delivering products/solutions in an applied setting (platform bring‑up, system integration, performance validation, deployment support, field issue resolution).
• Strong understanding of edge/IoT solution stacks: device, OS, middleware, connectivity, cloud/edge integration, and security considerations.
• Strong experience with AI frameworks such as PyTorch and Tensor Flow, including deploying and validating AI/ML and computer vision workloads on edge devices, with hands‑on performance tuning, quality troubleshooting, and field validation.
• Experience deploying and optimizing inference on hardware accelerators (CPU/GPU/ASIC/NPU), with understanding of inference systems and optimization for edge AI and/or data center platforms.
• Excellent C/C++/Python…