AI & Analytics Solutions Engineer
Hewlett Packard Enterprise
- Location
- Ft. Collins, Colorado, United States of America
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 167 approvals (FY2023)
- Posted
- Sep 2, 2026
Skills
About this role
AI & Analytics Solutions 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
The HPE Worldwide Hybrid Cloud Technology Acceleration Team is seeking a recent university graduate to join the AI & Analytics Solutions Engineering team. This is an early-career opportunity for someone interested in artificial intelligence, data analytics, enterprise technology, and solution development. In this role, you will work alongside experienced solution engineers, architects, product managers, and technical specialists to design, build, test, and document AI and analytics solutions running on HPE infrastructure. You will gain hands-on experience with modern technologies such as generative AI, retrieval-augmented generation (RAG), AI agents, data platforms, containers, Kubernetes, GPUs, virtualization, and hybrid cloud environments. The ideal candidate is curious, technically motivated, comfortable learning new technologies, and able to turn technical work into clear documentation and demonstrations. We are looking for someone with a strong technical foundation, a willingness to learn, and the ability to contribute effectively within a collaborative engineering team.
Responsibilities
Assist with the design, development, testing, and validation of AI and analytics solutions running on HPE infrastructure. Build foundational experience with generative AI, RAG, AI agents, model inference, data pipelines, vector databases, and analytics platforms. Support the deployment and testing of applications in containerized, virtualized, Kubernetes, GPU-enabled, and hybrid cloud environments. Work with senior engineers and technical specialists to translate solution requirements into testable configurations and use cases. Develop scripts, notebooks, APIs, and basic automation using Python and other relevant development tools. Execute documented test plans, capture results, and help identify technical issues, risks, and potential improvements. Create and maintain clear technical documentation, architecture diagrams, deployment instructions, demonstrations, and validation records. Contribute to field-ready materials such as solution playbooks, technical briefs, presentations, videos, blogs, demonstrations, and hands-on labs. Participate in technical reviews, team meetings, enablement sessions, and collaborative solution-development activities. Communicate progress, questions, challenges, and next steps clearly and consistently. Learn HPE technologies, products, solution-development processes, and enterprise infrastructure practices. Incorporate technical feedback and continuously improve the quality of assigned work. Support team priorities while developing greater technical ownership and independence over time.
Education
Recently completed a bachelor’s or master’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Computer Engineering, Information Systems, or a related technical field.
Required Qualifications
Foundational programming experience with Python gained through university coursework, academic research, internships, personal projects, or open-source contributions. Basic understanding of artificial