Lead Solutions Engineer – Cloud & AI

About the role

The Lead Solutions Engineer – Cloud & AI will act as a senior solution architect and presales professional, guiding enterprise customers through cloud, AI, data and private‑cloud transformations. Reporting to the Head of Presales, the role collaborates with a wide range of OEM and system‑integrator experts to design end‑to‑end solutions.

Key responsibilities

• Lead full‑cycle presales engagements for public, private, hybrid and multi‑cloud, AI infrastructure, data platforms and related ICT solutions.
• Engage customers to capture and qualify requirements across workloads, AI use cases, performance, security, scalability and governance.
• Design multi‑OEM architectures covering cloud platforms, GPU‑based AI infrastructure, data warehouses, lakes, lakehouses and private‑cloud services.
• Conduct workshops, technical presentations, discovery sessions, PoC discussions and respond to RFI/RFQ/RFPs with detailed sizing, BoQ/BoM and compliance matrices.
• Coordinate with networking, security, compute, storage, AI/ML and managed‑services SMEs to deliver integrated solutions.

Required profile

• 6‑8 years of enterprise cloud, AI, data‑platform or solution‑architecture experience.
• Bachelor’s degree in Computer Science, IT, Engineering, AI, Data Science or related field.
• Proven experience working with multiple OEM portfolios (NVIDIA, Dell, HPE, Lenovo, IBM, Cisco, VMware/Broadcom, Red Hat, Nutanix, Microsoft, AWS, Google Cloud, Oracle, Huawei, etc.).
• Hands‑on knowledge of GPU servers, AI workloads, container platforms (Kubernetes), virtualization and automation.
• Strong customer‑facing skills in requirement gathering, technical discovery, workshops and tender responses.

Required skills

• Public‑cloud platforms: AWS, Google Cloud, Microsoft Azure, Oracle Cloud.
• AI/ML infrastructure: NVIDIA GPUs, GPU clusters, high‑speed interconnects.
• Data platforms: data warehouse, data lake, lakehouse, ETL/ELT, analytics pipelines.
• Private‑cloud technologies: virtualization, software‑defined storage/networking, automation, orchestration.
• Containers & orchestration: Docker, Kubernetes.
• Relevant certifications (AWS, Azure, GCP, VMware, Red Hat, Nutanix, NVIDIA) are strongly preferred.