Senior Software Engineer

Overview

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.

Skills And Competencies

• Required: Advanced proficiency in Python, with experience building and operating production-grade data acquisition and extraction systems.
• Required: Strong hands-on experience in at least one additional language (e.g., Java, C#, Go, C++, or Rust) to inform sound system design.
• Required: Experience designing, deploying, and operating scalable and resilient pipelines with strong observability (monitoring, logging) and incident response practices.
• Required: Strong engineering discipline in continuous integration/continuous delivery, automated testing, and production readiness. Proven ability to run software in a production cloud environment (e.g., AWS, Azure),
• Required: Proven ability to deliver iteratively on a regular cadence (for example, biweekly releases) and improve reliability and performance over time.
• Preferred: Experience with web data acquisition, anti-bot techniques, and processing unstructured content (for example, HTML, PDF, XML) into validated structured datasets.
• Preferred: Experience integrating machine learning or large language model-based extraction approaches into production workflows.
• Preferred: Familiarity with Python async frameworks (asyncio) and web scraping tools (BeautifulSoup, Selenium/Playwright).
• Preferred: Experience with distributed processing, containerization (Docker/Kubernetes), and CI/CD tools (e.g., GitHub Actions, Airflow).
  
  

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
  
  

• Build and operate scalable web data acquisition and extraction pipelines, delivering high-quality structured datasets from complex unstructured sources.
• Design, build, and maintain production-grade data acquisition pipelines for global regulatory and government sources.
• Implement anti-bot and resilience strategies (for example, proxy rotation, headless browser automation, and CAPTCHA handling) to improve crawl success and stability.
• Build robust extraction workflows to process unstructured documents (for example, HTML, PDF, XML) into validated structured datasets.
• Integrate acquisition outputs with downstream enrichment workflows to support tagging, linkage, classification, and dataset usability.
• Deliver improvements and new production capabilities on a regular cadence (for example, every two weeks), including new sources, extraction enhancements, and reliability upgrades.
• Establish and maintain continuous integration/continuous delivery practices, including automated testing, monitoring, and operational runbooks as needed.
• Pilot and productionize at least one large language model-based parsing workflow, improving extraction accuracy for complex document types.
• Collaborate with machine learning engineers on prompt engineering and fine-tuning initiatives to enhance metadata extraction and entity resolution.
• Mentor junior and mid-level engineers on crawler and extractor best practices, pipeline architecture, and production operational standards.
• Implement feedback mechanisms (for example, tracking interfaces or application programming interfaces) so downstream consumers can submit corrections and enhancements, and use that feedback to drive continuous quality improvement.
  
  

Our Unstructured Data Team is responsible for building a cost-efficient, fast, self-service, controlled-risk data acquisition and extraction platform at scale.Our team contributes to Moody’s by:

• Delivering high-quality datasets from diverse web and regulatory sources to support strategic business and analytics use cases.
• Improving data freshness, reliability, and enrichment to increase downstream decision-making quality.
• Advancing automation capabilities, including production integration of large language models to improve extraction and entity resolution.
  
  

By joining our team, you will be part of exciting work in large-scale web data acquisition, unstructured document processing, data pipeline engineering, and production AI-assisted extraction across global source coverage.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.