Senior Solutions Architect (VMware & AI Platform)

Location: Riyadh, Saudi Arabia (On-site) Language Requirement: Fluent Arabic and English About Rackspace Technology Rackspace Technology™ is a leading end-to-end hybrid cloud and AI solutions company. We design, build, and operate our customers' cloud and AI environments across all major technology platforms, regardless of technology stack or deployment model. By partnering with customers throughout every stage of their cloud and AI journey, we enable application modernisation, AI adoption, innovation, and business transformation. Recognised by Glassdoor, Newsweek and Forbes as one of the best places to work, we attract and develop world-class talent committed to delivering our Fanatical Experience™ and helping customers stay ahead of what's next. The Role We are seeking a Senior Solutions Architect with deep expertise in VMware technologies, infrastructure modernisation, and AI platform enablement to support strategic sales opportunities across the Middle East region. In this presales-focused role, you will work closely with Sales, Solutions, and Delivery teams to design innovative solutions that address customers' datacentre modernisation, virtualisation, hybrid cloud, disaster recovery, business continuity, and platform transformation requirements — increasingly extended to include enterprise AI platforms. This means architecting GPU-as-a-Service (GPUaaS), model inference, and fine-tuning capabilities that run above the hypervisor layer, orchestrated through Kubernetes and integrated with VMware, together with the guardrails, resilience, and security controls such platforms demand. These solutions are often part of broader end-to-end engagements spanning managed services, security, networking, data platforms, and application modernisation. As a senior technical leader, you will act as a trusted advisor to customers while becoming a recognised subject matter expert within Rackspace for VMware, infrastructure modernisation, and AI platform solutions. Key Responsibilities • Develop trusted relationships with client executives and technical stakeholders, acting as both a business and technical advisor. • Lead customer workshops focused on VMware technologies, private cloud adoption, datacentre modernisation, hybrid cloud architectures, AI platform strategy, and platform transformation. • Design and position solutions leveraging VMware Cloud Foundation (VCF), vSphere, NSX, VMware Aria Suite, Tanzu, and complementary technologies. • Design and position AI platform solutions that layer GPUaaS, model serving/inference, and fine-tuning workloads above the hypervisor — for example VMware Private AI Foundation with NVIDIA on VCF, NVIDIA vGPU and Multi-Instance GPU (MIG) partitioning, and AMD Instinct accelerators — orchestrated through Kubernetes (VMware Tanzu / TKG). • Architect the AI serving and training stack above the platform layer, including inference servers and MLOps tooling (e.g. NVIDIA Triton, KServe, Ray, Kubeflow), GPU scheduling and multi-tenancy, model registries, and CI/CD pipelines for models. • Embed AI guardrails and governance into platform designs — including policy enforcement, content and prompt filtering, PII/data-loss controls, RAG safety patterns, and alignment with responsible-AI and regulatory frameworks (e.g. ISO/IEC 42001, EU AI Act, NCSC guidance) relevant to regulated and sovereign customers. • Design for resilience across the full stack — high availability, fault tolerance, backup, disaster recovery, GPU node-pool failover, training checkpointing, and continuity for stateful inference and data services. • Design for security and tenant isolation across the AI platform — network micro-segmentation (NSX), confidential computing, encryption of models and data in transit and at rest, secure model and container supply chains, secrets management, and identity/access controls. • Assess customer requirements and develop solution architectures that address current and future business objectives across both traditional infrastructure and AI workloads. • Lead complex presales engagements, coordinating with Subject Matter Experts (SMEs), Product Management, Sales, and Delivery teams. • Produce high-quality proposals, RFI/RFP responses, bids, and Statements of Work (SoWs) that clearly articulate customer requirements, solution designs, project scope, and delivery effort. • Provide specialist guidance on VMware platforms, AI infrastructure, migration strategies, infrastructure transformation, and hybrid cloud adoption. • Identify buying signals, compelling events, key stakeholders, and potential barriers to successful sales outcomes. • Anticipate and address technical and commercial objections, reducing customer risk and increasing confidence in Rackspace solutions. • Advise customers on infrastructure operations, AI platform operations, platform governance, cloud strategy, and transformation roadmaps. • Estimate project effort, resource requirements, and delivery approaches using Agile, Waterfall, or hybrid methodologies. • Maintain accurate pipeline, opportunity, and customer engagement information within Salesforce. • Contribute to the development of the wider solutions organisation through mentoring, knowledge sharing, and technical leadership. • Maintain deep expertise in VMware and AI platform technologies and stay current with industry developments and market trends. Required Qualifications & Experience • Bachelor's degree in Engineering, Computer Science, Information Systems, Business, or a related discipline; alternatively, 10+ years of relevant experience in technical presales, consulting, or solution architecture. • Extensive experience designing enterprise infrastructure and VMware-based solutions. • Strong understanding of datacentre and infrastructure modernisation strategies, including virtualisation, workload migration, consolidation, private cloud, and hybrid cloud adoption. • Proven expertise across VMware technologies, including: VMware Cloud Foundation (VCF), vSphere, vCenter, NSX, VMware Aria Operations and Automation, and VMware Tanzu. • Practical understanding of AI platform architecture running above the hypervisor, including GPUaaS provisioning and multi-tenancy, GPU virtualisation and partitioning (NVIDIA vGPU/MIG, GPU passthrough), and accelerator options across NVIDIA and AMD Instinct. • Working knowledge of the inference and fine-tuning stack — model serving and inference optimisation (throughput, latency, batching), fine-tuning and training workflows, and supporting MLOps tooling (e.g. Triton, KServe, Ray, Kubeflow). • Strong knowledge of Kubernetes and container platforms — particularly VMware Tanzu / TKG — as the orchestration layer for GPU-accelerated AI workloads. • Understanding of AI guardrails and governance, including policy enforcement, content/prompt safety, data protection, and alignment with frameworks such as ISO/IEC 42001, the EU AI Act, and NCSC guidance. • Strong knowledge of enterprise infrastructure architectures, including compute, storage, networking, and security. • Experience designing highly available, scalable, resilient, and secure virtualised and AI environments. • Understanding of disaster recovery, backup, business continuity, and infrastructure resilience sol