Senior Specialist, AI Validation

Vanguard

. Lead independent validation and challenge of AI/ML and generative AI models .

Posted 10/5/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI/ML model validation and risk management, with a strong focus on generative AI methodologies, compliance with internal standards, and effective communication of complex findings to diverse stakeholders.

Highest-signal resume keywords

PhD In A Quantitative DisciplineModel Validation ExperienceGenerative AI KnowledgePython ProgrammingRisk Management Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model DevelopmentModel ValidationAI/ML ModelingNLPDeep LearningEvaluation MethodologiesGenerative AI ArchitecturesCI/CDAlgorithmic Bias UnderstandingPrompt Engineering

Soft Skills

Exceptional Written CommunicationStakeholder ManagementFlexibilityExcellent Judgment

Industry Keywords

Financial Services SectorModel Risk ManagementGovernance ExpectationsModel LifecycleChange Management

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Lead independent validation and challenge of AI/ML and generative AI models
Assess models and systems using generative AI throughout their lifecycle, including ongoing monitoring, change management, and remediation of model risk findings
Challenge model assumptions, methodologies, data, testing, implementation, monitoring, and limitations
Assess compliance with internal AI standards, emerging regulatory requirements, and governance expectations, including fairness, explainability, transparency, and human oversight
Execute model validations and produce high-quality validation reports
Communicate validation findings to technical and non-technical stakeholders
Develop, maintain, and enhance risk-based validation procedures
Contribute to model risk management policies, standards, and procedures across the model lifecycle
Advise stakeholders on Model Risk policy and relevant standards
Identify emerging and top risks across the AI/ML and generative AI model portfolio and escalate them to MRM leadership
Coach and mentor junior team members
Participate in special projects and perform other assigned duties

Requirements

What you’ll need

PhD in a quantitative discipline such as Computer Science, Mathematics, Statistics, Physics, Engineering or an equivalent combination of training and experience
Minimum of 7 years of relevant experience in model development or model validation
Experience developing, testing or validating AI/ML models or systems using generative AI
Knowledge of programming languages including Python
Knowledge of technology platforms used for model development and deployment, including CI/CD
Knowledge of generative AI architectures including foundation models, RAG systems, agentic workflows, prompt engineering approaches, and associated risks such as hallucinations, algorithmic bias, and harmful outputs
Knowledge of AI/ML modeling including ML algorithms, NLP, deep learning, and evaluation methodologies
Exceptional written communication skills, including ability to communicate complex model risks to technical practitioners and senior executives
Experience in the financial services sector is a plus
Broad knowledge of risk management at financial institutions preferred
Ability to deal effectively with a variety of stakeholder teams
Ability to effectively manage multiple and competing priorities
Flexibility and excellent judgment

Benefits

Comp & perks

Hybrid working model
Visa sponsorship
In-person learning, collaboration, and connection
Opportunities to learn and develop skills