Описание
WHAT YOU'LL DO:
- Partner with stakeholders across Catalogue and Content, Product and Data to understand business problems, challenge existing processes, identify automation opportunities and translate them into practical solutions, from straightforward process automation to more complex AI-driven solutions;
- Own the full development lifecycle from initial problem framing and prototyping to production deployment, monitoring and ongoing optimization, including system design, testing, evaluation and continuous improvement;
- Build robust GenAI applications and LLM-based workflows leveraging RAG, structured outputs, function/tool calling, context management and multi-step reasoning workflows where appropriate;
- Construct and orchestrate reliable backend services and pipelines using Python, Apache Airflow, APIs and cloud-native solutions, optimizing for system reliability, latency and inference/token costs;
- Define and track operational metrics (throughput speed, error reduction, operational hours saved, metadata quality) to measure the tangible ROI of every deployed solution;
- Establish reusable patterns, practices and capabilities for building reliable, maintainable and scalable AI and automation solutions, implementing AI safety best practices (prompt injection defense, guardrails, output validation);
- Explore and prototype emerging AI capabilities, evaluating how they can solve real business problems and evolve into production-ready solutions;
- Help shape and expand our
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