GenAI Enablement Specialist

Business Enablement Vice President

J.P. Morgan is seeking a talented candidate as a Business Enablement Vice President for the Commercial & Investment Bank (CIB), with a focus on the firm's Payments and Banking businesses. The role sits within the CIB's Chief Data & Analytics Office (CDAO) and is at the Vice President 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 Vice President in the CIB's Chief Data & Analytics Office (CDAO), you will have a hands-on, applied AI role: you will sit shoulder-to-shoulder with senior business stakeholders in Payments and Banking, to understand daily workflows, and build working AI solutions against them fast with the tooling available internally. You will directly contribute to the CIB AI playbook and CIB libraries of re-usable components such as Prompt libraries and Skills. With a direct focus on Banking & Payments you will ensure that the practical, persona-level content produced by the team reaches the right business users in a consistent, high-quality, and discoverable way. You will write production-grade code and own the design of technical architecture of high-impact use cases from prototype through production. You will be a deep specialist in AI ML tooling available and you will bring that technical fluency to bear on real Payments and Banking problems. You will partner closely with Technology, business CDAO, and firmwide data science teams to design, deliver and scale what you build.

Job responsibilities

• Embed directly with senior stakeholders across Payments and Banking, observing real workflows and identifying the highest-leverage opportunities for GenAI to drive commercial impact
• Translate Payments and Banking domain context (cash management, treasury services, payments operations, M&A advisory, capital markets origination, credit, deal workflows) into precise technical requirements and where possible re-usable components for at scale adoption
• Design, prototype, and ship production AI Solutions against key business workflows with the available internal tooling and systems. Partner with Technology and CIB CDAO teams deliver Solutions in production that meet the firm's resilience, controls and risk standards
• Own end-to-end design, architecture and development for assigned use cases — data, retrieval, prompting, orchestration, evaluation, deployment, and ongoing iteration

Required qualifications, capabilities, and skills

• Background in capital markets origination, M&A advisory, treasury services, payments operations, or another core Payments/Banking domain. Knowledge of Financial Services required, with prior exposure to Payments and/or Banking workflows
• BSc or MSc degree in Computer Science, Engineering, Mathematics, or a related quantitative field
• Prior experience working directly with non-technical business stakeholders to scope, build, and ship technical solutions — Forward Deployed Engineering, solutions engineering, or analogous
• Hands-on experience writing and shipping production Python in an enterprise or high-bar engineering environment
• Demonstrable experience designing, building, and 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
• Outstanding ability to analyze problems and apply quantitative analytical approaches with excellent attention to detail
• Strong verbal and written communication skills; ability to communicate effectively and credibly with senior management, business users, and engineering counterparts