Data & AI Engineer

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Description

Accountabilities - Data Architecture and Engineering: Design, build, and maintain scalable data pipelines that integrate advertising performance, sales, engagement, and creator data from platforms such as TikTok, Meta, and other digital channels. - Backend Development: Develop robust data models, databases, and backend services using Python, Django, PostgreSQL, and SQL to support reliable data processing and platform functionality. - API Integrations: Connect third-party platforms and services, managing authentication, rate limits, complex data structures, and asynchronous workflows to ensure efficient and dependable data ingestion. - AI and Machine Learning Integration: Build and maintain LLM-powered workflows for video analysis, creative tagging, content classification, and AI-generated insights using models and services such as Gemini and Claude. - Semantic Search and Data Intelligence: Develop search and retrieval capabilities that transform large volumes of structured and unstructured data into relevant, actionable creative insights. - AI Performance Optimization: Improve the accuracy, reliability, scalability, and cost efficiency of AI-powered systems through effective prompt engineering, structured outputs, and continuous evaluation. - Product and Full-Stack Development: Build end-to-end features, including dashboards, search interfaces, content libraries, and reporting tools that connect creative performance with creator history and engagement data. - Cross-Functional

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