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frameworks. Familiarity with vector databases, semantic search, and agent-based AI solutions. Experience working with cloud-based AI platforms such as AWS SageMaker, Azure OpenAI, OpenAI APIs, and Google AI
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applications and tools, such as Java, Python, Jupyter Notebook, HTML, CSS, JavaScript, Git, APIs; Demonstrate knowledge of AWS and Google Colab; and Experience with Unix/Linux environment and high performance
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, and governance throughout Microsoft Fabric environments. Documentation - 10 Document data processes and workflows. API Integration - 10 Integrate and manage APIs to facilitate data exchange between
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out: Designing conversational flows for smart agents based on large language models (LLMs). Integrating external tools using APIs. Refining interaction prompts with language models, adjusting
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the major cloud providers (i.e. Amazon Web Services, Microsoft Azure, Google Cloud Platform) Advanced experience in installing, managing, updating, and troubleshooting Linux and Windows-based systems
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relational database systems, such as MySQL, Oracle or MS SQL Server Experience using and creating REST APIs Experience with Git source control Familiarity with iterative development practices, such as Agile
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the major cloud providers (i.e. Amazon Web Services, Microsoft Azure, Google Cloud Platform) Advanced experience in installing, managing, updating, and troubleshooting Linux and Windows-based systems
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user-friendly solutions. By working closely with AI educators, researchers, and student innovators, the Software Engineer will develop APIs, frameworks, MCP integrations, and automation that make AI
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a LINUX/UNIX and networked environment. Preferred Qualifications Experience working with NextJS to build SSR (Server Side Rendered) Applications, TypeScript, NextJS REST API and Database fetching
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research and/or development. Strong technical skills. Including experience with TensorFlow and/or PyTorch, API integration, and software development frameworks, and pipelines. Experience with deep learning