Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Help shape how AI is adopted across global businesses by turning real workflows into practical solutions. You will work hands-on with stakeholders to identify high-impact opportunities and rapidly build, test, and scale solutions using internal tools. This role offers broad exposure across Markets, Payments, Securities Services, and Global Banking while building deep fluency in modern AI and machine learning capabilities. You will contribute to reusable libraries and playbooks that help teams deliver consistent, high-quality outcomes. Join a team focused on measurable commercial impact and an innovation-forward culture.

As an AI Business Enablement Senior Associate in the AI Enablement team within the Chief Data and Analytics Office (CDAO), you will partner closely with business stakeholders to learn daily workflows and deliver applied AI solutions. You will translate domain context into clear technical requirements and reusable components that scale across teams. You will design, build, and ship AI solutions from prototype through production in partnership with Technology and data science teams. You will contribute to shared libraries, including prompt libraries and skills, so persona-level content is consistent, high-quality, and easy to discover. You will help ensure solutions meet the firm's resilience, controls, and risk standards.

Job Responsibilities
- Partner with stakeholders across Commercial and Investment Bank businesses to observe workflows and identify high-leverage generative AI opportunities
- Translate business domain context across Markets, Banking, Payments, and Securities Services into clear technical requirements and reusable components
- Prototype and deliver production AI solutions using internal tooling and systems, partnering with Technology and Chief Data and Analytics Office teams to meet resilience, controls, and risk standards
- Contribute to end-to-end design, development, and iteration across data, retrieval, prompting, orchestration, evaluation, and deployment for assigned use cases

Experience
- Knowledge of financial services with exposure to one or more core commercial and investment banking domains, such as capital markets, advisory, treasury services, payments operations, markets, or securities services
- Experience partnering with non-technical business stakeholders to scope, build, and deliver technical solutions, including solutions engineering or forward-deployed engineering
- Hands-on experience writing and shipping Python in a professional engineering environment
- Experience designing, building, or deploying large language model applications, including prompting, evaluation, retrieval-augmented generation, and agentic orchestration
- Familiarity with the modern generative AI stack, including large language model APIs, vector stores, embeddings, tool or function calling, multi-step agent design, and evaluation

About you
- Analytical and problem-solving skills with strong attention to detail
- Verbal and written communication skills, with the ability to communicate effectively with business users, engineering counterparts, and management

Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field