Storage AI Engineer
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Job Description
Structured overview of role & requirementsAbout This Role
Design and build production-grade AI and Generative AI solutions using LLMs, including AI agents, copilots, and workflow automation systems.
Develop and optimize Retrieval-Augmented Generation (RAG) architectures with vector databases and enterprise knowledge bases for scalable AI model deployment.
Establish monitoring, observability, and governance for responsible AI usage while driving experimentation and adoption of emerging AI technologies across the organization.
Minimum Requirements
Bachelor's or master's degree in computer science, engineering, or closely related quantitative discipline.
3-5 years of relevant work experience in AI/ML and software engineering.
Proven programming skills in Python, SQL, and Java or Go.
Experience with AI/ML frameworks such as PyTorch, Scikit-learn and cloud platforms like AWS/Azure, including container technologies (Kubernetes, Docker).
Ideal Candidate Profile
Experienced engineer skilled at integrating machine learning and generative AI into enterprise storage or cloud platforms.
Comfortable working in a hybrid environment with cross-functional collaboration including data scientists and engineering teams.
Strong technical expertise in productionizing AI, including fine-tuning foundation models, prompt engineering, and deployment automation (MLOps).