JazzWorld FDE
Lead Solutions Engineering (Cloud & AI)
- Location Islamabad, Islamabad Capital Territory, Pakistan
- Type Full-time
- Team B2B Marketing & Products
- Seniority senior
- Posted 2026-10-05
Original posting ↗ You apply on the company site — we never collect applications.
Extracted automatically from public job postings. Always verify details on the original posting before applying.
role details
Leads end-to-end presales engagements for enterprise cloud, AI, data platform solutions, generating and qualifying customer requirements.
Summary generated by AI from the original posting.
Hard requirements to check first
- Clearance：not mentioned in the posting
- Work auth：not mentioned in the posting
- Travel：customer-facing; travel not stated
Skills
DockerAWSGCPNVIDIADell TechnologiesHPELenovoIBMCiscoVMware/BroadcomRed Hat
Excerpt from the original posting
Grade Level: L3 Location: Islamabad Last date to apply: 11th October 2026 What is Lead Solutions Engineering – Cloud & AI? A senior solution architect and presales professional responsible for enterprise cloud, AI, data and private cloud solution discovery, architecture, qualification and customer engagement across multiple OEM portfolios. The role will generate requirements with customers, develop end-to-end cloud, AI and data solutions, lead technical engagements and coordinate multiple OEM/SI subject matter experts to address complex enterprise cloud transformation, AI infrastructure, data platform and private cloud requirements. The role reports directly to the Head of Presales- SI & Manage Services and works closely with extended Cloud, AI, data, compute, storage, data center, security, network, OEM and SI subject matter experts. What does Lead Solutions Engineering – Cloud & AI? Key responsibilities • Lead end-to-end presales engagements for enterprise cloud, AI, data platform, data warehouse, data lake, private cloud and related ICT solutions. • Engage customers to generate and qualify requirements across business applications, workloads, data, AI use cases, performance, security, availability, scalability, governance and operational dimensions. • Design multi-OEM cloud and AI architecture covering public cloud, private cloud, hybrid/multi-cloud, cloud-native platforms, virtualization, container platforms, AI infrastructure and enterprise data platforms. • Demonstrate strong working knowledge across multiple OEM portfolios, including NVIDIA, Dell Technologies, HPE, Lenovo, IBM, Cisco, VMware/Broadcom, Red Hat, Nutanix, Microsoft, AWS, Google Cloud, Oracle, Huawei and equivalent cloud, AI, compute and data platform vendors. • Develop high-level and low-level architectures, workload sizing, compute/GPU sizing, storage and networking requirements, data platform architecture, capacity calculations, BoQ/BoM and technical compliance matrices. • Understand different cloud flavours and deployment models, including public cloud, private cloud, hybrid cloud, multi-cloud, hosted cloud, sovereign/residency-oriented cloud and cloud-native/containerized environments. • Assess and translate AI use cases into solution architectures, including generative AI, machine learning, inference, training, computer vision, NLP, analytics and enterprise AI workloads. • Develop AI infrastructure designs covering GPU servers, GPU clusters, CPU infrastructure, high-performance ne…