Description

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

• Deep hands-on experience building and improving AI powered RAG-based legal/financial document extraction (chunking, indexing, metadata, grounding, citation discipline).
• Strong knowledge of NLP, Machine Learning, embeddings, vector databases (indexing, ingestion/re-indexing, filtering etc.) and semantic search and similarity analysis with proven retrieval optimization skills and prompt engineering skills.
• Solid experience integrating LLM APIs, including context-window budgeting, prompt/version management, and turning structured input to structured outputs.
• Hands-on work with agentic workflows: tool calling, multi-step orchestration, memory/state management, MCP and subagent etc.
• Ability to build a rigorous evaluation framework for AI generated output.
• Strong python skills and working proficiency in SQL or equivalent database query and management tools.

Education

• Master's degree in Finance, Artificial Intelligence, Data Science, Information Technology, or related field.
• PhD complete or in progress (preferred).
• 5-10+ years of experience in Finance, Fixed Income, Structured Finance and Private Credit (preferred).
• 3+ years of experience building and delivering AI-enabled data and document processing solutions with proven, hands-on track record of improving accuracy, consistency and production reliability.

Responsibilities

In this role you will be a member of the Asset Management Business Unit AI Squad, managing and supporting AI related innovations of the industry's leading workflow solutions. We are seeking a highly skilled and experienced Associate Director Level Financial Engineer to join AI squad team on a part-time basis (limited duration, and/or minimum of 20 hours/week) focusing on AI enabled projects. This role will be responsible for supporting hands-on improvements to our AI driven projects such as advanced RAG, MCPs and Agentic workflows. The role requires strong technical proficiency in applied generative artificial intelligence, data-driven experimentation, vector database, semantic similarity analysis as well as a strong understanding of financial markets and instruments.

• Lead end-to-end support and improvements to financial document RAG pipeline (document parsing, retrieval, extraction, validation, and structured outputs).
• Design and optimize embedding-based retrieval and vector database operations.
• Improve retrieval quality using advanced configurations to reduce missed terms and incorrect extractions.
• Implement agentic workflows, including reasoning, tool calling, multi-step orchestration, and state and memory management to handle complex documents and edge cases.
• Working with QA team to build and maintain a rigorous AI results evaluation framework, including benchmark datasets, labelling guidelines, metrics, regression tests, and experiment tracking.
• Analyze extraction errors, develop an error taxonomy, and translate findings into prioritized fixes balancing quality, latency, and cost.
• Help test and enhance Structured Finance/ Private Credit domain-specific Model Context Protocol implementation to improve tool reliability, tool selection, and end-to-end agentic workflow performance.
• Collaborate with AI squad team, product, engineering, and domain stakeholders to clarify requirements, communicate progress, and document designs, decisions, and deliverables.

About the team

Join the Asset Management Business Unit AI squad team at Moody's Analytics. We're building cutting edge and innovative AI powered solutions to service asset managers in exciting use cases across the financial markets. Our collaborative environment values transparency, quality, and innovation. As part of this team, you'll help shape the direction for innovation, new and existing products and make a meaningful impact on our clients and the industry.

For US-based roles only: the anticipated hiring base salary range for this position is $118,300.00 - $194,850.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role may be eligible for a completion bonus. Moody's also offers insurance and a discounted employee stock purchase plan for limited duration employees.

Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody's also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email accommodations@moodys.com. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications.

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

Click here to view our full EEO policy statement . Click here for more information on your EEO rights under the law . Click here to view our Pay Transparency Nondiscrimination statement . Click here to view our Notice to New York City Applicants.
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.
For more information on the Securities Trading Program, please refer to the STP Quick Reference guide on ComplianceNet

Please note: STP categories are assigned by the hiring teams and are subject to change over the course of an employee's tenure with Moody's.
Requisition #: 12160

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