AI Validation, Senior Specialist
Vanguard is hiring an AI Validation, Senior Specialist. Level rates it ; you can apply on Vanguard.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions visa sponsorship.
- The posting mentions prompt engineering, RAG and AI agents among its tools and skills.
- Vanguard has 327 other open roles on Level.
- Posted in the last few days.
AI in this role
The Model Risk Management (MRM) Team, part of Vanguard’s second line of defense, is seeking an experienced model risk professional to support independent oversight of AI/ML and generative AI models built and/or used across the enterprise.
Vanguard is a global investment management firm with a mission to give investors the best chance for investment success. Across its businesses and support functions, Vanguard uses AI to drive effectiveness, efficiency, and a range of key business outcomes.
In this role, you will lead the independent validation and challenge of AI models, ensuring they are conceptually sound, well‑governed, and fit for purpose. You will work closely with data scientists, quantitative developers, model users, and technology partners, providing credible challenge while maintaining strong, collaborative relationships with the business.
Beyond individual model reviews, you will help drive the evolution of Vanguard’s model risk management framework, shaping methodologies, standards, and practices that support consistent, enterprise‑wide application of model risk principles.
Core Responsibilities
Assess models and systems using generative AI throughout their lifecycle including leading independent validations and assessment of ongoing monitoring, change management, and remediations of model risk findings
Provide effective challenge of model assumptions, methodologies, data, testing, implementation, monitoring and limitations, with a focus on material risk drivers
Assess compliance with internal AI standards, emerging regulatory requirements, and governance expectations related to AI/ML and generative AI systems, including fairness, explainability, transparency, and human oversight
Ensure timely execution of model validation and high-quality validation reports that meet internal standards, and communicate validation findings clearly to technical and non‑technical stakeholders
Develop, maintain and enhance validation procedures to support a consistent, risk-based approach for independent validation and effective challenge of AI/ML and generative AI systems, including keeping informed of the evolution of technology in generative and agentic AI
Contribute to the design and enhancement of model risk management policies, standards, and procedures across the full model lifecycle (inventory, development, validation, approval, and ongoing monitoring)
Support the MRM team in advising stakeholders on Model Risk policy and other relevant standards as needed
Identify emerging and top risks across the portfolio of AI/ML and generative AI models and surface them to MRM leadership
Provide coaching and mentorship to junior team members
Participate in special projects and perform other duties as assigned
Qualifications
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 is required
Knowledge of programming languages including Python is a requirement
Knowledge of technology platforms used for model development and deployment, CI/CD is a requirement
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 are required, including the ability to communicate complex model risks to audiences ranging from technical practitioners to 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
Exhibits flexibility and excellent judgment
Special Factors
Sponsorship
Vanguard is offering visa sponsorship for this position.About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
How we rate this
AI Validation, Senior Specialist at Vanguard rates 82 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI agents, and NLP. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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