Director Unstructured Presales Storage Leader

Director Unstructured Presales Storage Leader This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office. Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE. Job Description: We are seeking a strategic and technically grounded Pre-Sales Leader to drive the next phase of growth for our X10K AI data platform business. This leader will own the pre-sales strategy, execution, and enablement required to accelerate customer adoption of AI Factory solutions across RAG, inference, and model training workloads. The role combines customer engagement, technical leadership, sales execution, team development, and cross-functional influence. You will partner closely with enterprise customers, account teams, solution architects, partners, and Product Management to shape high-value opportunities, develop compelling solution architectures, and build repeatable go-to-market motions. A data-first perspective is essential. You will guide customers in understanding how data is created, moved, enriched, accessed, and consumed across AI pipelines, positioning infrastructure and data platforms as enablers of business value rather than as the starting point of the conversation. The ideal candidate brings strong commercial judgment, deep understanding of AI and data architectures, and the ability to lead teams through complex enterprise sales cycles across APAC and EMEA. You will help identify the right opportunities at the right time, align solutions to customer readiness and workload requirements, and ensure we win where we can deliver sustainable, measurable impact. This is not a pure storage role. However, a strong understanding of how modern data platforms and storage technologies enable AI pipelines is essential. Key Responsibilities Pre-Sales Strategy and Leadership Define and execute the pre-sales strategy for the X10K AI data platform business. Partner with sales leadership to develop account strategies, territory plans, pipeline priorities, and opportunity qualification criteria. Establish repeatable approaches for identifying, shaping, qualifying, and advancing AI Factory opportunities. Apply strong technical and commercial judgment to prioritize opportunities based on customer readiness, workload fit, scale, competitive position, and likelihood of long-term success. Drive consistency in pre-sales execution, forecasting, deal inspection, technical validation, and executive engagement. Establish and track measures such as pipeline contribution, deal velocity, win rate, solution adoption, and customer outcomes. Customer Engagement and Deal Leadership Lead strategic customer engagements with CTOs, CIOs, Heads of AI, Data Engineering leaders, and other executive stakeholders. Direct technical discovery sessions to understand business objectives, data characteristics, AI workloads, existing environments, and desired outcomes. Translate customer requirements into scalable AI architectures and compelling business-aligned solution designs. Guide pre-sales teams through complex, multi-stakeholder enterprise sales cycles. Serve as an executive-level technical advisor throughout the opportunity lifecycle. Align technical solutions to measurable business outcomes, including performance, cost efficiency, reliability, scalability, and time to value. Help sales teams position solutions with precision and credibility, ensuring that proposed architectures are fit for purpose. Data-Centric AI Architecture Lead architecture discussions based on data requirements and lifecycle considerations, including: Data volume, velocity, variety, and distribution Structured and unstructured data Data locality, gravity, and movement patterns Data access, governance, metadata, and retrieval requirements Ensure solution designs optimize: Sequential versus random access patterns Batch versus real-time processing Data movement between storage, compute, and model layers Metadata, indexing, and retrieval efficiency for RAG Performance, cost, reliability, and trustworthiness Evaluate how data architecture decisions affect: Model performance and accuracy Latency and time-to-first-token GPU utilization Data ingestion and preparation requirements Overall operating cost and scalability AI Solution Architecture, Sizing, and Validation Lead the development and validation of AI Factory architectures for: Retrieval-Augmented Generation Model inference and deployment Model training and fine-tuning Guide teams in sizing environments based on: GPU counts and configurations Data volumes and throughput requirements Model types and workload characteristics Ingestion, retrieval, and serving requirements Define performance expectations across the full AI pipeline. Establish methodologies for evaluating time-to-first-token, throughput, GPU efficiency, data access performance, and cost. Ensure proposed designs are technically sound, commercially viable, and aligned with customer requirements. Support proof-of-concept, benchmark, and technical validation activities where required. X10K Data Platform Positioning Define and articulate the strategic value of X10K within modern AI architectures. Position data platforms as critical enablers of AI performance, scalability, reliability, and operational efficiency. Guide teams in positioning: Object storage and S3-based architectures Data pipelines and pipeline simplification or elimination strategies Vector databases and retrieval architectures AI frameworks and model-serving environments Hybrid and cloud-integrated AI deployments Align messaging and solution positioning to customer-specific data scale, access patterns, performance requirements, and business priorities. Help differentiate X10K through value-based conversations rather than infrastructure-only discussions. Field Enablement and Team Development Build the capabilities of pre-sales teams through coaching, mentoring, structured deal reviews, and technical enablement. Create repeatable tools and assets, including: Discovery frameworks Qualification criteria Reference architectures Solution blueprints Sizing methodologies Competitive positioning Business-value models Enable account teams to confidently position AI solutions with both technical and executive audiences. Develop and deliver internal training, workshops, technical briefings, and field readiness programs. Promote consistent practices for customer discovery, architecture development, technical validation, and executive communication. Cross-Functional Leadership Partner closely with Product Management to: Influence roadmap priorities across RAG, inference, and training use cases Provide structured feedback on customer requirements and solution gaps Identify competitive trends and market opportunities Improve product-market fit and field readiness Collaborate with Engineering, Marketing, Professional Services, Partners, and Customer Success to improve the complete customer experience. Create and present high-impact technical content, including reference architectures, design patterns, whitepapers, conference presentations, and internal or external publications. Represent the company and X10K at customer events, industry forums, partner engagements, and executive briefings. Required Qualifications 10+ years of experience in technical pre-sales, solutions architecture, sales engineering leadership, field CTO, or a related customer-facing technology leadership role. Demonstrated experience leading and developing pre-sales or solutions architecture teams across APAC and EMEA regions Proven track record of influencing complex enterprise sales cycles and contributing to pipeline growth, revenue, win rates, or deal velocity. Strong understanding of AI/ML workflows, including: Retrieval-Augmented Generation Model inference and deployment Model training and fine-tuning Ability to lead architecture from data requirements, data behavior, and access patterns rather than from an infrastructure-first approach. Experience mapping and optimizing end-to-end data flows across the AI lifecycle, from ingestion and preparation through retrieval, model interaction, and feedback loops. Experience designing or positioning GPU-based environments for AI workloads. Strong understanding of data architecture concepts, including: Data pipelines Data lakes Object storage Metadata and indexing High-performance data access Demonstrated ability to evaluate solution fit and articulate trade-offs across performance, cost, complexity, risk, and scalability. Proven ability to lead executive-level customer discovery and translate business requirements into technical solutions. Experience partnering with Product Management and Engineering to influence product direction, roadmap priorities, and solution development. Strong commercial acumen, including opportunity qualification, value articulation, competitive positioning, and sales execution. Excellent communication, presentation, negotiation, and executive engagement skills. Preferred Qualifications Experience leading pre-sales for AI infrastructure, data platforms, cloud, or enterprise technology solutions. Exposure to high-performance computing or distributed compute environments. Familiarity with AI/ML frameworks and ecosystems, such as PyTorch, TensorFlow, vector databases, and model-serving platforms. Experience with cloud, hybrid, and on-premises AI architectures. Background in object storage, high-throughput data platforms, or storage technologies. Experience building or scaling pre-sales organizations and go-to-market programs. Experience developing sales methodologies, qualification frameworks, enablement programs, and technical field assets. Experience collaborating with strategic partners and technology alliances. What Success Looks Like A healthy, well-qualified pipeline of high-value AI Factory opportunities. Consistent pre-sales execution across regions, accounts, and sales teams. Improved deal velocity, win rates, forecast accuracy, and revenue contribution. Stronger field confidence in positioning and selling X10K AI data platform solutions. Clear, differentiated, and business-aligned customer messaging. Repeatable methodologies for discovery, qualification, architecture, sizing, validation, and executive engagement. High-performing pre-sales teams with strong technical depth and commercial discipline. Increased customer adoption of X10K across RAG, inference, and training workloads. Product and roadmap decisions informed by structured, actionable field feedback. Customer solutions that deliver measurable improvements in performance, cost efficiency, scalability, reliability, and time to value. Accessibility HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here . Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability. What We Can Offer You: Health & Wellbeing We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing. Personal & Professional Development We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division. Unconditional Inclusion We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. Let's Stay Connected: Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE. 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