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integrations using the Model Context Protocol (MCP).\n\n- Integrate vector databases and search technologies into production systems.\n\n- Develop responsive frontend features and connect them to backend APIs.\n\n- Evaluate AI output quality, retrieval relevance, latency, and cost; improve performance and reliability.\n\n- Implement authentication, authorization, logging, testing, and monitoring.\n\n- Apply software engineering best practices, including SOLID principles and design patterns, to build scalable, maintainable systems.\n\n- Deploy and operate LLMs in on-premises environments using inference servers such as vLLM or SGLang.\n\n- Collaborate with product, design, and engineering teams to turn requirements into production-ready features.\n\n- Document technical decisions and contribute to code reviews and engineering standards.\n\nRequired Qualifications:\n\n- Professional experience developing full-stack web applications.\n\n- Strong Python skills and experience with 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