Storage AI Engineer
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Job Description
Structured overview of role & requirementsAbout This Role
Design and develop production-grade AI and Generative AI solutions, including large language models and Retrieval-Augmented Generation (RAG) architectures.
Develop AI agents, copilots, workflow automation systems, and scalable APIs/services for AI models in production environments.
Implement monitoring, observability, and governance mechanisms ensuring responsible and optimized AI deployment at enterprise scale.
Minimum Requirements
Bachelor's or master's degree in computer science, engineering, or closely related quantitative field.
3-5 years of relevant work experience.
Proficiency in AI/ML programming languages and frameworks: Python, SQL, Java, Go, PyTorch, Scikit-learn.
Experience with AI/ML technologies including Generative AI (GPT, Claude, Llama), LangChain, prompt engineering, fine-tuning, vector databases, cloud platforms (AWS/Azure), Kubernetes, Docker, MLflow, and CI/CD.
Ideal Candidate Profile
Strong technical background bridging machine learning, generative AI, and cloud technologies applied to Storage domain solutions.
Experience building scalable AI-powered products integrating complex agent ecosystems and enterprise knowledge sources.
Ability to work independently applying subject matter expertise and collaborating with data science and engineering teams on AI innovation and deployment at scale.