Storage AI Engineer

Overview

Build enterprise-scale AI solutions and complex agent ecosystems for real-world Storage applications. Work at the intersection of machine learning, generative AI, software engineering, and cloud technologies to create scalable AI-powered products and platforms.

What you'll do

• 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.
• Collaborate with data scientists and engineering teams to bring advanced AI capabilities into real-world Storage applications.

What you'll need

• Bachelor's or master's degree in computer science, engineering or closely related quantitative discipline.
• Typically, 3-5 years’ experience.
• Knowledge of Programming, Python, SQL, and Java, Go.
• Knowledge of AI/ML, PyTorch, and Scikit-learn.
• Knowledge of LangChain and Generative AI.
• Knowledge of GPT, Claude, and Llama.
• Knowledge of Prompt Engineering, Fine-tuning, RAG, Agentic AI, and Vector Databases.
• Knowledge of Cloud & MLOps.
• Knowledge of Public Cloud (AWS/Azure), Kubernetes, Docker, MLflow, and CI/CD.

Nice to have

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

Details

• Location: Bengaluru, Karnātaka, India.
• Hybrid role requiring an average of 2 days per week from an HPE office.