The A&PS AI Solution Architect is a senior technical leadership role responsible for shaping, selling, and delivering end-to-end AI solutions for HPE customers. The role spans the full lifecycle from presales solution design through delivery assurance, ensuring AI architectures are technically sound, commercially viable, and deliver measurable business outcomes.
This role works closely with A&PS Geo Presales teams, account teams, partners, and delivery organizations to translate customer business challenges into scalable AI solutions built on HPE platforms, including AI Factory, Hybrid Cloud, HPC, data platforms, and partner ecosystems.
Key Responsibilities
Presales & Solution Shaping
- Lead the design of AI solutions aligned to customer business outcomes, leveraging HPE infrastructure, software, and services portfolios.
- Partner with A&PS Geo Solution Architects, Sales, and GBUs to define AI architectures, use cases, and roadmaps.
- Own the technical content for Statements of Work (SoWs), including scope definition, assumptions, dependencies, risks, and success criteria.
- Contribute to solution pricing, effort estimation, and risk assessment to ensure commercially viable proposals.
- Act as a trusted advisor to customers, articulating HPE's AI value proposition and differentiating capabilities.
Delivery Engagement & Assurance
- Provide architectural leadership during delivery, ensuring solutions designed in presales are implemented as intended.
- Partner with Project Managers and Lead Delivery Architects to manage technical risks, dependencies, and design changes.
- Support design reviews, technical governance, and key customer checkpoints throughout delivery.
- Ensure solutions are delivered within the agreed scope, cost model, and quality standards.
- Contribute to resolution of complex technical issues and escalation management when required.
Technical Leadership & Innovation
- Maintain deep expertise in AI/ML architectures, data pipelines, model lifecycle management, and MLOps.
- Apply best practices across AI Factory, hybrid cloud, data management, security, and governance.
- Contribute to the evolution of A&PS AI offerings, reference architectures, and reusable assets.
- Support enablement of presales and delivery teams through knowledge sharing and mentoring.
- Stay current with industry trends, emerging technologies, and competitive landscapes in AI and data.
Stakeholder Collaboration
- Work closely with A&PS, GBUs, Sales, Partners, and Delivery teams across geographies.
- Engage with senior customer stakeholders, including CIO, CTO, CDO, and AI leaders.
- Collaborate with partners and ISVs to integrate complementary AI technologies where appropriate.
Required Experience & Skills
- Proven experience as a Solution Architect, AI Architect, or similar role in enterprise environments.
- Strong understanding of AI/ML platforms, data architectures, and model lifecycle management.
- Experience designing solutions across hybrid cloud, on-prem, and edge environments.
- Solid knowledge of enterprise infrastructure, networking, security, and data platforms.
- Experience supporting presales activities, including SoWs, solution costing, and customer presentations.
- Ability to translate complex technical concepts into clear business value.
- Strong stakeholder management, communication, and influencing skills.
Preferred Qualifications
- PhD degree in Computer Science, Data Science, Engineering, Mathematics, Physics or related field and 5+ years of relevant experience.
- OR Master's Degree in these areas and at least 8 years of relevant experience.
- Hands-on experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, Kubernetes, MLOps platforms).
- Background in consulting or professional services delivery environments.
- Industry vertical experience (e.g., Manufacturing, Financial Services, Healthcare, Transportation, Public Sector, Telco, Energy) is a strong plus, enabling effective alignment of AI solutions to industry-specific use cases and regulatory requirements.
- Relevant certifications in cloud, AI/ML, data platforms, or enterprise architecture are an advantage.
Success Measures
- Quality, scalability, and reusability of AI solution designs.
- Win-rate and success of AI-related pursuits.
- Delivery outcomes, including customer satisfaction and avoidance of delivery escalations.
- Contribution to growth and maturity of the A&PS AI portfolio.
