Pre-Sales Solutions Architect

该职位来源于猎聘 About the Role We are looking for an experienced and commercially minded Senior Pre-Sales Solutions Architect to lead our Cloud and AI transformation practice. In this strategic, customer-facing role, you will serve as a trusted technical advisor to enterprise clients, shaping solution direction across compute, storage, hybrid cloud, and AI infrastructure. You will work at the intersection of technology strategy and business outcomes — translating complex technical capabilities into compelling, differentiated propositions. Key Role Responsibilities

• Architect and propose Cloud and AI transformation solutions tailored to individual customer needs, encompassing infrastructure design, platform selection, and service delivery models
• Engage in pre-sales activities including technical workshops, proof-of-concept scoping, and strategic client meetings to define and validate solution direction
• Promote and position partner technologies (GPU, Cloud) and internal service offerings to maximize customer value and commercial outcomes
• Develop trusted advisor relationships with enterprise stakeholders including C-suite, IT leadership, and procurement teams
• Lead technical governance and quality assurance across solution design and delivery engagements, ensuring alignment to architecture standards and best practices
• Represent the business at industry events, partner forums, and technology briefings to build market profile and stay ahead of emerging trends
• Mentor internal teams, contribute to knowledge-sharing initiatives, and drive continuous improvement of pre-sales methodology and documentation Location:
• Shenzhen, Guangdong Key Attributes Required Experience & Background
• Minimum 5 years' experience in a pre-sales, solutions architecture, or technical consulting role within an enterprise IT environment
• Proven track record of designing and delivering enterprise AI systems, infrastructure solutions, and professional services engagements
• Demonstrated success engaging senior stakeholders and translating business requirements into viable technical solutions Technical Knowledge
• Strong knowledge of Cloud & AI architecture and hybrid infrastructure solutions, including hands-on familiarity with leading platforms: – Compute & Storage:

Server architecture and technology – AI & ML Infrastructure: GPU-accelerated compute (NVIDIA DGX/HGX), AI training and inference platforms, MLOps and data pipelines – Hybrid Infrastructure: hyperconverged infrastructure (HCI), software-defined storage (SDS), composable architecture

• Strong understanding of public cloud platforms (Azure, AWS, Google Cloud) and data centre modernization strategies including cloud migration, lift-and-shift, and cloud-native transformation
• Strong understanding of AI and ML solutions, with familiarity with frameworks, enabling the design of AI solutions based on customer business scenarios.
• Strong knowledge of GPU computing and GPU server architectures, including AI training and inference infrastructure built on platforms such as NVIDIA GPUs, with the ability to recommend suitable compute infrastructure for customers.
• Familiarity with service management frameworks, technical documentation standards, and vendor tools relevant to solution delivery Soft Skills & Professional Competencies
• Excellent client engagement, presentation, and stakeholder management skills — comfortable presenting at board and C-suite level
• Strong written and verbal communication skills in English; able to produce high-quality proposals, architecture documents, and executive briefings
• Commercially aware with the ability to build business cases, articulate ROI, and position solutions competitively
• Self-motivated, collaborative, and able to manage multiple concurrent opportunities in a fast-paced environment Preferred Qualifications
• Industry certifications such as AWS Solutions Architect, Azure Solutions Expert, Google Cloud Professional, HPE Master ASE, Dell Certified, or equivalent
• Experience with AI/ML frameworks and tools including TensorFlow, PyTorch, vLLM etc.
• Background in professional services scoping, including effort estimation, SOW development, and delivery methodology
• Prior experience working with channel partners, OEMs, or system integrators in a vendor or reseller environment