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You still may be a great fit for this role or other open roles.\n\nWe are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.\n\nSkills and Competencies :\n\n- 7+ years of software engineering experience with 5+ years in Data Engineering, including advanced Python expertise for building scalable, production-grade solutions\n\n- Proven experience designing and optimizing Retrieval-Augmented Generation (RAG) pipelines, hybrid search strategies, vector databases, embedding models, and evaluation frameworks\n\n- Strong knowledge of large-scale data engineering, including ETL/ELT development, batch and streaming pipelines, distributed computing frameworks, and workflow orchestration tools such as Airflow, Prefect, or Dagster\n\n- Hands-on experience integrating REST/GraphQL APIs, implementing caching solutions, and applying data privacy, security, and access-control best practices\n\n- Proficiency with modern AI frameworks and libraries including LangChain, LangGraph, Pandas, NumPy, Polars, and Pydantic\n\n- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency\n\n- Proven ability to implement AI-powered solutions to solve business challenges.\n\n- Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use\n\nEducation :\n\n- Bachelor's, Master's, or PhD degree in Computer Science, Information Technology, Artificial Intelligence, or a related discipline\n\n- AI-related certifications are preferred\n\nResponsibilities :\n\n- Design, develop, and maintain scalable data engineering solutions that support AI-driven products and services\n\n- Architect and optimize advanced retrieval systems, including RAG pipelines, vector search platforms, and embedding strategies\n\n- Develop and manage large-scale batch and streaming data pipelines while ensuring data quality, reliability, and performance\n\n- Establish retrieval evaluation frameworks and continuously improve search relevance, latency, and operational efficiency\n\n- Integrate external data sources and APIs, leveraging caching and performance optimization techniques where appropriate\n\n- Champion best practices in data engineering, AI solution development, security, documentation, and stakeholder communication\n\nAbout the Team :\n\nThe Asset Management Technology team within Moody's Analytics develops innovative software, advanced analytics, and AI-driven solutions that support investment decision-making in the Structured Finance domain.\n\nWorking within a global, cross-functional environment, the team leverages modern technologies to build scalable, future-ready products that help clients manage risk and identify opportunities in evolving financial markets.\n\nMoody's is an equal opportunity 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