AVP ML and GenAI Model Validation

Job Description

Purpose of the role

To validate and approve models for specific usages both at inception and on a periodic basis, and of model changes, as well as conducting annual reviews. 

Accountabilities

• Validation of models for their intended use and scope, commensurate with the complexity and materiality of the models.
• Approval or rejection of a model or usage based on assessment of the model’s conceptual soundness, performance under intended use and the clarity of the documentation of the model’s inherent risks, limitations and weaknesses.
• Assessment of any compensating controls used to mitigate Model risk.
• Documentation of validation findings and recommendations in clear and concise reports, providing actionable insights for model improvement.
• Evaluation of the coherence of model interactions and quality of Large Model Framework aggregate results that generate output for regulatory submissions or management decision making and planning.
• Design of the framework and methodology to measure and, where possible, quantify model risk, including the assessment of framework level uncertainty.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Embark on a transformative journey as an AVP ML and GenAI Model Validation at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences.

To be successful in this role, you should possess the following skillsets:

•  Highly numerate, evidenced by an Honours degree, master’s, or PhD (or equivalent) in a quantitative discipline such as Computer Science, Mathematics, Physics, Operational Research, Economics, Engineering, or Finance.
• Experience developing, validating, or independently reviewing best‑in‑class tools and AI/ML models for large financial institutions or comparable regulated environments, with the ability to effectively challenge and improve model methodologies and model management processes.
• Strong analytical and technical expertise in AI/ML modelling, including experience with ML algorithms (e.g., XGBoost, LightGBM, Random Forest), NLP models, and deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Experience developing or validating AI/ML models on large datasets in Hadoop/AWS environments.
• Designed, fine‑tuned, and shipped Generative AI models - transformer‑based LLMs, RAG systems for grounded retrieval, and GANs-using PyTorch/TensorFlow and Hugging Face, including prompt engineering, RLHF, and rigorous evaluation of GenAI models.
• Hands‑on experience with Generative AI technologies, including Large Language Models, Transformers, retrieval‑augmented generation (RAG), and prompt‑based systems; familiarity with LangChain and LangGraph.
• Experience designing, developing, validating, or reviewing agent‑based AI architectures, including multi‑agent orchestration, task planning, memory management, and safeguard mechanisms.
• Sound understanding of financial services regulatory expectations and model risk guidance (e.g., SR 11‑7, SS1/23, IFRS 9, EU AI Act etc.).
• Strong communication and influencing skills, with the ability to produce high‑quality written material for both technical and senior non‑technical audiences.
• Highly organised, with strong attention to documentation quality, governance requirements, and follow‑through on actions.

Some other highly valued skills include:

• Experience developing or validating customer‑facing or material GenAI/agentic AI use cases, including chatbots, document generation, summarisation, and decision‑support tools.
• Prior exposure to model risk management activities such as inception validation, periodic validation, annual reviews, and material model change assessments.
• Familiarity with Responsible AI practices, including fairness, bias detection and mitigation, explainability, human‑in‑the‑loop controls, and broader ethical AI considerations.
• Exposure to agentic AI systems, orchestration frameworks, and multi‑model workflows.
• Relevant certifications or formal training in Generative AI, Large Language Models (LLMs), or Machine Learning.
• Ability to work effectively within a high‑performing, globally‑distributed team, and to collaborate across diverse technical and control functions.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role is based in our Noida office.