Lead Solutions Engineering (Cloud & AI)

JazzWorld; Islamabad; On-site; PKR 4,000,000 - 6,500,000; Full time

Job summary

Jazz in Islamabad is seeking a Lead Solutions Engineer - Cloud & AI to drive enterprise cloud, AI, data platform and private cloud architecture across multiple OEM portfolios. You will lead presales engagements, gather requirements, size workloads, and coordinate SME teams to deliver end-to-end solutions.

The role requires 6–8 years in enterprise cloud/AI, a Bachelor’s or higher in a relevant field, and strong multi-OEM experience. Hybrid/onsite with global tech partners.

Qualifications

• 6-8 years of relevant enterprise cloud, AI, data platform, solution architecture, presales or technical consulting experience.
• Bachelor's degree or higher in Computer Science, IT, Computer Engineering, AI, Data Science, Cloud Computing or another relevant technology discipline.
• Strong multi-OEM experience across cloud, compute, AI infrastructure, data platforms and private cloud technologies, including NVIDIA, HPE, Dell Technologies, Lenovo, IBM, Cisco, VMware/Broadcom, Red Hat, Nutanix, Microsoft, AWS, Google Cloud, Oracle, Huawei and/or equivalent vendors.
• Strong understanding of cloud deployment models and architectures, including public cloud, private cloud, hybrid cloud, multi-cloud

Responsibilities

• Lead end-to-end presales engagements for enterprise cloud, AI and data platforms.
• 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 cloud, multi-cloud, hosted cloud and cloud-native environments.
• Coordinate with OEMs, distributors and SI partners to validate designs and support commercial proposals.
• Lead customer workshops, technical presentations, discovery sessions and PoC discussions to drive opportunities.

Education

Bachelor's degree or higher in Computer Science, IT, Computer Engineering, AI, Data Science, Cloud Computing

Job description

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 networking, high-performance storage, virtualization/containerization, orchestration and AI application platforms.
• Design and position enterprise data platforms covering data warehouses, data lakes, lakehouse architectures, data integration, ETL/ELT, analytics, data governance and AI/ML data pipelines.
• Design private cloud platforms covering compute, virtualization, software-defined storage/networking, automation, orchestration, self-service, multi-tenancy, monitoring, backup/DR and lifecycle management.
• Lead customer workshops, technical presentations, discovery sessions, solution demonstrations, PoC discussions and AI/cloud use-case workshops.
• Prepare and lead technical responses for RFI/RFQ/RFP/tender opportunities, including requirement analysis, compliance mapping, technical deviations, assumptions, sizing and solution narratives.
• Work with OEMs, distributors, authorized OEM partners and system integrators to validate designs, obtain technical clarifications, develop configurations and support commercial proposals.
• Coordinate with networking, security, compute, storage, data center, application, database, AI/ML and managed services SMEs to create integrated end-to-end solutions.
• Identify opportunities for cloud transformation, AI adoption, data modernization, private cloud, analytics and emerging technology adoption by understanding customer environments, technology gaps and future requirements.
• Support account teams in opportunity qualification, solution positioning, technical differentiation and customer engagement strategy without limiting solutions to a single OEM.
• Maintain current knowledge of cloud architectures, AI infrastructure, GPU technologies, data platforms, private cloud, containers/Kubernetes, automation, observability, cloud security, FinOps and emerging AI/cloud technologies.

Key Deliverables

• Customer requirement, discovery and workload/use-case assessment documents.
• End-to-end cloud, AI, data platform and private cloud architecture and solution designs.
• GPU/compute sizing, storage and networking requirements, capacity calculations and BoQ/BoM.
• Data warehouse, data lake/lakehouse and AI/ML platform architecture recommendations.
• Private cloud platform designs covering virtualization/containerization, automation, orchestration, self-service, HA and DR.
• RFI/RFQ/RFP/tender technical responses, compliance matrices, deviations, assumptions and technical clarifications.
• Customer presentations, workshops, demonstrations, AI/cloud use-case sessions and PoC plans.
• OEM/SI technical engagement, solution validation, configuration recommendations and reference architectures.
• Cross-domain solution architecture and SME coordination across cloud, AI, data, compute, storage, network and security.
• Opportunity-specific technical proposals, solution narratives and business-aligned technology recommendations.

Jazz is an equal opportunity employer. We celebrate, support, and thrive on diversity and are committed to creating an inclusive environment for all employees.

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 networking, high-performance storage, virtualization/containerization, orchestration and AI application platforms.
• Design and position enterprise data platforms covering data warehouses, data lakes, lakehouse architectures, data integration, ETL/ELT, analytics, data governance and AI/ML data pipelines.
• Design private cloud platforms covering compute, virtualization, software-defined storage/networking, automation, orchestration, self-service, multi-tenancy, monitoring, backup/DR and lifecycle management.
• Lead customer workshops, technical presentations, discovery sessions, solution demonstrations, PoC discussions and AI/cloud use-case workshops.
• Prepare and lead technical responses for RFI/RFQ/RFP/tender opportunities, including requirement analysis, compliance mapping, technical deviations, assumptions, sizing and solution narratives.
• Work with OEMs, distributors, authorized OEM partners and system integrators to validate designs, obtain technical clarifications, develop configurations and support commercial proposals.
• Coordinate with networking, security, compute, storage, data center, application, database, AI/ML and managed services SMEs to create integrated end-to-end solutions.
• Identify opportunities for cloud transformation, AI adoption, data modernization, private cloud, analytics and emerging technology adoption by understanding customer environments, technology gaps and future requirements.
• Support account teams in opportunity qualification, solution positioning, technical differentiation and customer engagement strategy without limiting solutions to a single OEM.
• Maintain current knowledge of cloud architectures, AI infrastructure, GPU technologies, data platforms, private cloud, containers/Kubernetes, automation, observability, cloud security, FinOps and emerging AI/cloud technologies.

Key Deliverables

• Customer requirement, discovery and workload/use-case assessment documents.
• End-to-end cloud, AI, data platform and private cloud architecture and solution designs.
• GPU/compute sizing, storage and networking requirements, capacity calculations and BoQ/BoM.
• Data warehouse, data lake/lakehouse and AI/ML platform architecture recommendations.
• Private cloud platform designs covering virtualization/containerization, automation, orchestration, self-service, HA and DR.
• RFI/RFQ/RFP/tender technical responses, compliance matrices, deviations, assumptions and technical clarifications.
• Customer presentations, workshops, demonstrations, AI/cloud use-case sessions and PoC plans.
• OEM/SI technical engagement, solution validation, configuration recommendations and reference architectures.
• Cross-domain solution architecture and SME coordination across cloud, AI, data, compute, storage, network and security.
• Opportunity-specific technical proposals, solution narratives and business-aligned technology recommendations.

Jazz is an equal opportunity employer. We celebrate, support, and thrive on diversity and are committed to creating an inclusive environment for all employees.

Grade Level: L3

Location: Islamabad

Last date to apply: 11th October 2026

Requirements

What are we looking for and what does it need to be Lead Solutions Engineering - Cloud & AI?

Experience and Educational requirements

• 6-8 years of relevant enterprise cloud, AI, data platform, solution architecture, presales or technical consulting experience.
• Bachelor's degree or higher in Computer Science, IT, Computer Engineering, AI, Data Science, Cloud Computing or another relevant technology discipline.
• Strong multi-OEM experience across cloud, compute, AI infrastructure, data platforms and private cloud technologies, including NVIDIA, HPE, Dell Technologies, Lenovo, IBM, Cisco, VMware/Broadcom, Red Hat, Nutanix, Microsoft, AWS, Google Cloud, Oracle, Huawei and/or equivalent vendors.
• Strong understanding of cloud deployment models and architectures, including public cloud, private cloud, hybrid cloud, multi-cloud