Vice President - Modeling & Quant Analytics; MRG), AI & Agentic Model Validation

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.

• A deep understanding of AI model risk management, including risks and controls specific to Generative AI and agentic AI, and their implications for model validation and governance
• Genuine, hands‑on depth in agentic AI with a demonstrated track record of building, deploying and evaluating AI agents and multi‑agent systems, including tool use, orchestration and state management using modern agent frameworks
• Strong, hands‑on knowledge of agent evaluation, including task‑success and trajectory testing, grounding and retrieval quality assessment, hallucination and drift detection, robustness testing, benchmarking, bias and fairness assessment, alignment and misalignment analysis, adversarial testing, and red‑teaming
• Strong LLM and Generative AI engineering fluency, including prompting strategies, retrieval‑augmented generation, context and memory design, function and tool calling, guardrails, observability, and failure‑mode analysis
• Track record of taking advanced AI systems from prototype to production, with attention to reliability, safety, and responsible AI controls
• Proficiency in programming languages such as R, Python, MATLAB, and SQL, with the ability to work within an established codebase; knowledge of C++ programming is preferred
• Experience in model validation, model risk management, or independent review is advantageous, with prior work in credit, counter party, or market risk considered helpful context
• Typically 10+ years of relevant professional experience spanning AI, machine learning, quantitative analytics, software engineering, model risk management, or related disciplines, including significant hands‑on experience with advanced AI and agentic systems
• Senior leadership presence with the ability to set a clear vision, coach and mentor colleagues, build trusted relationships, and promote a growth mindset and effective challenge
• Highly organized, efficient, and detail‑oriented, able to prioritize competing demands, work to tight deadlines, and deliver accurate, high‑quality outputs independently and collaboratively
• A strong communicator, able to articulate complex ideas clearly for both technical and non‑technical audiences, with strong written and spoken English
• 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.

• A strong academic background in a technical or quantitative field such as computer science, artificial intelligence, machine learning, mathematics, physics, or engineering, with a preference for candidates holding a postgraduate degree
• Demonstrated, hands‑on agentic AI capability is weighted alongside formal credentials

Lead the independent evaluation and challenge of models, scorecards, and agents used in credit rating activities across asset classes while advancing AI model risk management and governance…