Storage AI Engineer

We are seeking a Storage AI Engineer to join our Hybrid Cloud team, leading the innovation agenda and technology roadmap for all of HPE. As a Storage AI Engineer, you will deliver enterprise-scale AI solutions, build complex agent ecosystems, and work at the intersection of machine learning, generative AI, software engineering, and cloud technologies to build scalable AI-powered products and platforms.

Key Responsibilities

• Design and build production-grade AI and Generative AI solutions using large language models (LLMs).
• Develop AI agents, copilots, and workflow automation systems that improve user productivity and business outcomes.
• Implement Retrieval-Augmented Generation (RAG) architectures using vector databases and enterprise knowledge sources.
• Fine-tune, evaluate, and optimize machine learning and foundation models for accuracy, performance, safety, and cost.
• Build scalable APIs, services, and platforms to serve AI models in production environments.
• Establish monitoring, observability, and governance mechanisms to ensure responsible AI deployment.
• Drive experimentation, innovation, and adoption of emerging AI technologies across the organization.

Education and Experience Required

• Bachelor's or master's degree in computer science, engineering, or a closely related quantitative discipline.
• Typically, 3-5 years' experience.

Knowledge and Skills

• Programming: Python, SQL, Java, Go
• AI/ML: PyTorch, Scikit-learn, LangChain
• Generative AI: GPT, Claude, Llama, Prompt Engineering, Fine-tuning, RAG, Agentic AI, Vector Databases
• Cloud & MLOps: Public Cloud (AWS/Azure), Kubernetes, Docker, MLflow, CI/CD

Good To Have Skills

• Storage Domain Skills (Block/Object/File Storage)
• MLOps and LLMOps platform experience.