Senior Private Cloud AI Engineer - Staff Engineer

Senior Private Cloud AI Engineer - Staff Engineer 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: HPE Hybrid Cloud, we lead the innovation agenda and technology roadmap for all of HPE. This includes managing the design, development, and product portfolio of our next-generation cloud platform, Green Lake. Working with customers, we help them reimagine their information technology needs to deliver a simple, consumable solution that helps them drive their business results. Join us redefine what’s next for you.  What you’ll do: Key Responsibilities Platform Engineering & Development Design, develop, and enhance components of the HPE Private Cloud AI platform. Build automation, tooling, APIs, and workflows that improve deployment, operations, monitoring, and lifecycle management. Contribute to Kubernetes-based platform services and cloud-native capabilities. Participate in architecture reviews, design discussions, and technical roadmap planning. AI Platform Enablement Support integration of AI technologies into the platform. Enable workloads leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), model serving frameworks, and MLOps tools. Evaluate and integrate emerging AI technologies, frameworks, and development tools. Assist in testing, validating, and operationalizing AI workloads on enterprise infrastructure. Infrastructure & Systems Integration Collaborate across compute, networking, storage, virtualization, and operating system domains to deliver end-to-end solutions. Assist with platform integration, deployment validation, performance tuning, and troubleshooting. Identify and resolve system-level issues spanning hardware, infrastructure, platform software, and applications. Contribute to infrastructure automation and operational efficiency initiatives. Customer & Solution Engineering Partner with product management, support, field engineering, and customer teams to address real-world deployment challenges. Investigate customer-reported issues, identify root causes, and drive resolution across engineering teams. Support proof-of-concepts, reference architectures, and customer adoption initiatives.