Job DescriptionJ.P. Morgan is seeking a talented candidate as a Business Enablement Senior Associate for the Commercial & Investment Bank (CIB). The role sits within the CIB's Chief Data & Analytics Office (CDAO) and is at the Senior Associate level, reporting into the AI Enablement - Head of Business Enablement.
The CIB AI Enablement team is responsible for driving the adoption of AI and accelerating the analytics agenda globally across Markets, Payments, Securities Services, and Global Banking - driving the integration of AI into business workflows to deliver measurable commercial impact. The responsibilities of the Chief Data & Analytics Office include advancing both traditional AI/ML and generative AI capabilities, identifying priorities and focusing on high-impact AI use cases, setting the GenAI strategy around LLMs and Agentic AI, reusing and scaling AI solutions across lines of business, and fostering a culture of innovation and an AI-first mindset among employees.
As a Business Enablement Senior Associate on the AI Enablement team, you will play a hands-on, applied AI role across a range of CIB businesses. Working with business stakeholders, you will learn daily workflows and rapidly build AI solutions using internal tooling. You will contribute to the CIB AI playbook and reusable libraries (e.g., prompt libraries and skills) to ensure persona-level content is consistent, high-quality, and easy to discover. You will write quality code and help design technical solutions for high-impact use cases from prototype through production. You will build fluency in AI/ML tooling and partner with Technology, business CDAO, and firmwide data science teams to deliver, scale, and operationalize your solutions.
Job responsibilities- Work directly with stakeholders across CIB businesses, observing real workflows and helping identify high-leverage opportunities for GenAI to drive commercial impact
- Translate business domain context (across Markets, Banking, Payments & Securities Services) into clear technical requirements and, where possible, re-usable components for adoption at scale
- Prototype and ship production AI solutions against key business workflows using available internal tooling and systems; partner with Technology and CIB CDAO teams to deliver solutions in production that meet the firm's resilience, controls, and risk standards
- Contribute to end-to-end design, development, and iteration for assigned use cases - spanning data, retrieval, prompting, orchestration, evaluation, and deployment
Required qualifications, capabilities, and skills- Knowledge of Financial Services, with exposure to one or more core CIB domains (e.g., capital markets, advisory, treasury services, payments operations, markets, or securities services)
- BSc or MSc degree in Computer Science, Engineering, Mathematics, or a related quantitative field
- Experience working with non-technical business stakeholders to scope, build, and ship technical solutions - solutions engineering, forward-deployed engineering, or analogous
- Hands-on experience writing and shipping Python in a professional engineering environment
- Experience designing, building, or deploying LLM-based applications: prompt engineering, evaluation, retrieval-augmented generation (RAG), and agentic frameworks/orchestration
- Familiarity with the modern GenAI stack: LLM APIs, vector stores, embeddings, tool/function calling, multi-step agent design, and LLM evaluation
- Strong analytical and problem-solving ability, with excellent attention to detail
- Strong verbal and written communication skills; ability to communicate effectively with business users, engineering counterparts, and management
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About the TeamJ.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
