
QA Risk AI/ML Model Developer AVP
Barclays • London, England, United Kingdom
Role & seniority: Assistant Vice President (Quant AI/ML Model Developer) within QA; leads or influences complex AI/ML initiatives in a greenfield Quant AI/ML team.
Stack/tools: Python with AI/ML model development (including generative AI); large language models, prompt engineering, retrieval augmented generation (RAG) pipelines, vector databases; knowledge of platforms such as Bedrock; collaboration with tech for data, environments, and tooling.
Top 3 responsibilities
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Design, develop, implement, and support mathematical, statistical, and ML models and analytics for business decision‑making.
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Collaborate with technology to specify dependencies (data, environments, tools) and operationalize analytics/models; ensure documentation and validation.
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Maintain ongoing effectiveness and governance (risk controls, model risk policies) and provide stakeholder‑facing communication.
Must-have skills
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Python programming with AI/ML model implementation (ideally including generative AI).
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Experience with LLMs, prompt engineering, RAG pipelines, or vector databases.
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Quantitative/technical background with a relevant degree (e.g., computer science, math, physics).
Nice-to-haves
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Understanding of GenAI landscape, model options, and platforms (e.g., Bedrock).
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Banking/financial services experience; ability to simplify complex concepts for diverse stakeholders.
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Strong communication and collaboration skills; risk and controls mindset.
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Location &
Full Description
Build the next generation of AI‑driven risk solutions at Barclays. This is a rare opportunity to join a new Quant AI/ML team within QA, focused on developing cutting‑edge generative AI applications that will transform how risk and finance functions operate. You’ll work on high‑impact projects—from payment systems to credit and finance use cases—while shaping the bank’s approach to large language models, vector databases, and next‑generation AI tooling. If you’re excited by innovation, hands‑on model development, and the chance to influence a greenfield capability, this role offers an exceptional platform to grow.
To be successful as a Quant AI / ML Model Developer, you should have experience with
Python programming and implementing AI/ML models, ideally including generative AI. Working with large language models, prompt engineering, RAG pipelines, or vector databases. Applying quantitative or technical skills gained through a relevant degree (e.g., computer science, maths, physics).
Some Other Highly Valued Skills May Include
Understanding of the GenAI landscape, including model options, implementation details, and platforms such as Bedrock. Familiarity with financial services or experience working in a banking environment. Strong communication skills to simplify complex technical concepts for diverse stakeholders.
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
Location: London
Purpose of the role
To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making
Accountabilities
Design analytics and modelling solutions to complex business problems using domain expertise. Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools. Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams. Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them. Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users. Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy. Ensure all development activities are undertaken within the defined control environment.
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.