Senior AI Solutions Architect
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Role details
Tech stack
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Requirements
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Enterprise AI & Data Strategy: Strong architectural knowledge of modern data platforms (Databricks, Lakehouse architecture) and Generative AI patterns (RAG, agentic workflows, multi-model evaluation frameworks).
- Business Acumen: Ability to translate complex technical concepts into clear business ROI for non-technical executives and brand leaders.
- Technical Background: Prior hands-on experience in data engineering, AI/ML, or enterprise cloud solutions, enabling effective oversight of technical teams and architectural decisions.
Required Skills
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Data Platforms & Cloud Ecosystems: Deep understanding of modern cloud data architectures, distributed data processing, enterprise data governance, and scalable storage layers.
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Generative AI & Intelligent Systems: Hands-on experience with LLM orchestration frameworks, retrieval-augmented generation (RAG) patterns, vector databases, and multi-model evaluation pipelines.
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Data Integration & Pipeline Engineering: Strong background in integrating enterprise data sources, master product catalogs, unstructured files, and third-party REST APIs into centralized data environments.
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Software Engineering & Data Analysis: Proficiency in Python, SQL optimization, structured data validation, and building robust API-driven workflows.
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Prepare application
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