Distinguished Technologist, Private Cloud AI

Experteer Overview In this role you will shape the AI strategy for HPE’s Private Cloud AI offerings, acting as a hands-on senior architect and AI leader. You will define architectures across private and hybrid cloud environments, influence partner technologies, and drive production-grade AI capabilities. You’ll lead cross-functional design workshops, mentor engineers, and translate complex AI concepts into scalable, trustworthy solutions. This is a high-impact, customer-facing position that blends technical depth with strategic leadership. You will work with global teams to push PCAI forward, enabling cutting-edge AI to run securely at scale. Compensation / Benefits * Lead AI architecture and design workshops to shape PCAI strategy * Define customer-ready AI architectures for private and hybrid cloud, including models, runtimes, and governance * Evaluate ISV technologies for the AI platform stack and drive architectural decisions * Design multi-agent, LLMOps/AgentOps, and AI security/governance blueprints for reliable AI systems * Build reusable AI components and agents, collaborating with engineering to scale POCs into production * Troubleshoot and optimize AI systems at scale and establish best practices for model lifecycle and responsible AI * Create high-impact technical content to influence customers, partners, and stakeholders * Mentor senior engineers and architects across multiple teams Tasks * Bachelor’s degree in computer science or relevant field * 15+ years of progressive technical leadership and architectural experience * At least 2 years designing and implementing production-ready scaled Agentic/Generative AI solutions * At least 2 years designing agentic AI/Generative AI platforms used by multiple solutions * 5+ years designing, engineering, and operating large-scale AI/ML on a major public cloud * Deep knowledge of cloud-native AI services, open-source tech, and third-party tools * Expert understanding of AI technologies from public cloud providers, open source, and vendors * Hands-on experience with foundation models, LLMs, RAG pipelines, multi-agent systems, and tool-using agents * Experience with knowledge graphs, semantic layers, AI security, governance, and observability * Proficiency in cloud-native architectures (Kubernetes, containers, microservices) and distributed platforms * Ability to lead through influence and communicate complex topics to executives and technical audiences Key requirements * Health & wellbeing * Personal & professional development * Unconditional inclusion * Flexible work arrangements * Career growth opportunities * Competitive compensation

2026-08-06, blueprints for reliable AI systems * Build reusable AI components and agents, collaborating with engineering to scale POCs into production * Troubleshoot and optimize AI systems at scale and establish best practices for model lifecycle and responsible AI * Create high-impact technical content to influence customers, partners, and stakeholders * Mentor senior engineers and architects across multiple teams Tasks * Bachelor’s degree in computer science or relevant field * 15+ years of progressive technical leadership and architectural experience * At least 2 years designing and implementing production-ready scaled Agentic/Generative AI solutions * At least 2 years designing agentic AI/Generative AI platforms used by multiple solutions * 5+ years designing, engineering, and operating large-scale AI/ML on a major public cloud * Deep knowledge of cloud-native AI services, open-source tech, and third-party tools * Expert understanding of AI technologies from public cloud providers, open source, and vendors * Hands-on experience with foundation models, LLMs, RAG pipelines, multi-agent systems, and tool-using agents * Experience with knowledge graphs, semantic layers, AI security, governance, and observability * Proficiency in cloud-native architectures (Kubernetes, containers, microservices) and distributed platforms * Ability to lead through influence and communicate complex topics to executives and technical audiences Key requirements * Health & wellbeing * Personal & professional development * Unconditional inclusion * Flexible work arrangements * Career growth opportunities * Competitive compensation