Senior Data & AI Engineer

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We 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.

• Design, implement, and maintain intelligent AI agents and multi agent workflows using LangChain, Copilot Studio, and Microsoft AI and machine learning services.
• Develop, manage, and optimize data pipelines and architectures using Microsoft Fabric as the primary platform, including Fabric Lakehouse, Data Pipelines, Dataflows Gen2, OneLake, or Synapse Analytics, with Microsoft Azure services used in conjunction.
• Translate business requirements into scalable AI and data solutions, including data modeling, prompt engineering, agent orchestration, and workflow automation.
• Write high quality, secure, and maintainable code using Python with PySpark, Structured Query Language, and supporting frameworks, while leading and participating in code reviews and enforcing engineering best practices.
• Monitor AI agent pipelines and data workflows, troubleshoot issues, perform root cause analysis, and implement durable solutions to ensure reliability and performance.
• Work closely with business, product, and technical teams to prioritize work, align solutions with business goals, and communicate technical concepts clearly and effectively.
• Guide and mentor junior engineers and developers, providing feedback, design guidance, and best practices for both data engineering and AI solutions.
• Stay current with emerging AI, cloud, and data engineering technologies, and evaluate new tools and frameworks for potential integration into enterprise solutions.
• Ensure solutions adhere to data governance, security, and enterprise compliance standards, and maintain clear documentation for data models, pipelines, and AI workflows.
• Maintain source code repositories and automated build and deployment pipelines using GitHub or Azure DevOps to support reliable and repeatable releases.
• Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization.

• 5+ years of industry experience in designing and operating enterprise scale data platforms, using Microsoft Fabric as the primary platform, including Fabric Lakehouse, Dataflows Gen2, OneLake or Synapse Analytics, with Microsoft Azure services used in conjunction, required to deliver scalable, reliable, and high performance data foundations aligned with business objectives.
• Strong hands on technical capability in Python, PySpark, and Structured Query Language, required to build robust, maintainable data pipelines, transformations, and integrations that support analytics and AI driven workloads.
• Proven ability to design and build agent based and generative artificial intelligence solutions, using Microsoft agentic frameworks and services such as Copilot Studio, LangChain, and Azure OpenAI services, with working knowledge of similar AI platforms across other cloud providers such as Amazon Bedrock or Google Vertex AI considered a good to have.
• Deep understanding of software engineering, cloud architecture, and operational practices, including version control, continuous integration and continuous delivery, secure coding, testing, documentation, and software development life cycle methodologies such as Agile and hybrid models, required to maintain high engineering standards, reliability, and governance.
• Strong analytical and problem solving skills, required to diagnose complex data and system issues, design effective solutions, and make sound technical decisions in high impact, production environments.
• Demonstrated technical leadership, collaboration, and mentoring abilities, required to partner closely with business and technical stakeholders, translate requirements into scalable solutions, guide junior engineers, and contribute to the successful delivery of highly visible enterprise initiatives.
• Bachelor’s or higher degree in Computer Science or a related technical field.

• Medical, Personal Accident, Life Insurance and Time Off.