Customer Engineering, Field Engineer & Solutions Architect, Staff - UAE
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Key skills for this role
About the Role
Qualcomm is seeking a Staff Solutions Engineer to lead edge AI initiatives, from pre-sales solutioning to post-sales technical success. The role requires deep expertise in AI models, edge deployment, and cross-functional collaboration.
Key Skills for This Role
Responsibilities
- 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 + connectivity
- Build and maintain reusable technical assets (reference architectures, demo scripts, BOM guidance, integration patterns)
- Partner with internal engineering/product teams to translate customer needs into actionable technical requirements
- Support sales by leading technical engagements: architecture reviews, technical workshops, competitive positioning discussions, and stakeholder presentations
- Own technical responses for customer facing deliverables (e.g., technical proposals, solution narratives, pilot plans)
- Coordinate cross functional execution (BD, engineering, PMO, partners) to keep pilots and deal critical milestones on track
- 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
- Enable customer and partner teams via structured technical training and practical handover artifacts
- Support transition from pilot to production by defining deployment prerequisites
- Act as the technical escalation point during early deployments
Requirements
- 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
- Proven ability to build and support AI embedded/edge deployments
- Hands on experience delivering products/solutions in an applied setting
- Strong understanding of edge/IoT solution stacks
- Strong experience with AI frameworks such as PyTorch and TensorFlow
- Experience deploying and optimizing inference on hardware accelerators
- Excellent C/C++/Python programming and software design skills
- Solid understanding of inference hardware constraints and system level performance bottlenecks
- Hands on expertise with Linux based systems, low level software, drivers, and systems bring up
- Experience developing/deploying Linux solutions using containers and orchestration (e.g., Docker/Kubernetes), plus source code/config management (Git)
- Excellent communication skills
Full Job Posting
General Summary
- Qualcomm is enabling a world where everyone and everything can be intelligently connected.
- We are seeking a Staff Solutions Engineer to support executing the portfolio of edge initiatives by translating customer opportunities into shippable solutions from solution definition to demo/pilot execution and into commercial deployment readiness.
- This role spans the full lifecycle: pre‑sales solutioning, sales enablement, and post‑sales technical success.
What You’ll Do
- 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 + connectivity, including feasibility assessments and “fit to platform” recommendations.
- Build and maintain reusable technical assets (reference architectures, demo scripts, BOM guidance, integration patterns) that accelerate field execution and repeatability.
- Partner with internal engineering/product teams to translate customer needs into actionable technical requirements, while providing structured feedback based on field learnings.
- Support sales by leading technical engagements: architecture reviews, technical workshops, competitive positioning discussions, and stakeholder presentations, ensuring technical clarity and risk closure.
- Own technical responses for customer facing deliverables (e.g., technical proposals, solution narratives, pilot plans), ensuring alignment to 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, and maintaining customer confidence through clear communication.
Required Qualifications
- 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, including ecosystem integration experience across customer engineering, internal business units, and partners to drive aligned, end to end execution.
- Hands on experience delivering products/solutions in an applied setting (platform bring up, system integration, performance validation, deployment support, and field issue resolution).
- Strong understanding of edge/IoT solution stacks: device + OS + middleware + connectivity + cloud/edge integration + security considerations.
- Strong experience with AI frameworks such as PyTorch and TensorFlow, 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 (or equivalent) programming and software design skills, including debugging, profiling, and performance analysis.
- Solid understanding of inference hardware constraints and system level performance bottlenecks (memory bandwidth, latency/throughput tradeoffs, thermal/power constraints).
- Hands on expertise with Linux based systems, low level software, drivers, and systems bring up.
- Experience developing/deploying Linux solutions using containers and orchestration (e.g., Docker/Kubernetes), plus source code/config management (Git).
- Excellent communication skills: ability to translate complex technical details into clear customer facing narratives and executive ready updates.
Preferred Qualifications
- Experience enabling, deploying, or supporting solutions on Qualcomm SoC based systems (IoT/edge/compute) and translating customer requirements into actionable platform execution.
- Exposure to Qualcomm compute ecosystems (e.g., Snapdragon class platforms), including subsystem level understanding (CPU/GPU/NPU/modem/connectivity) and customer enablement patterns.
- Familiarity with Qualcomm accelerated inference platforms (e.g AI100) or comparable data center/edge inference accelerators, with strong end to end architecture understanding across edge to core environments.
- Understanding of wireless connectivity considerations for edge deployments, including cellular communication technologies and filed integration dependencies.
What's On Offer
- Salary including housing & transport allowance
- Stock (RSU's) and performance related bonus
- 16 weeks fully paid Maternity Leave
- 6 weeks fully paid Paternity Leave
- Employee stock purchase scheme
- Child Education Allowance
- Relocation and immigration support (if needed)
- Life and Medical Insurance
- Live+ Well Reimbursement for health and recreational membership fees
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