AI Product Lead

A leading global financial services organization is building a dedicated AI capability within its Investment Banking organization and is seeking an AI Product Lead who can bridge deep business understanding with hands-on technical execution. This is not a traditional product-management or requirements-gathering role. You will work directly with senior AI leadership and Investment Banking professionals to identify high-value opportunities, rapidly prototype AI-powered applications, validate their business impact, and help drive successful solutions into production and adoption. The ideal candidate brings experience from Investment Banking or a closely adjacent deal-oriented financial environment and has developed genuine hands‑on capability building LLM-powered applications. You should understand how bankers work while also being technically credible with engineers. Responsibilities Identify high‑friction Investment Banking workflows and translate them into practical AI opportunities. Design and build AI‑powered tools supporting workflows such as pitch preparation, comparable‑company analysis, diligence, document preparation, client research, and market surveillance. Own the early product lifecycle from opportunity identification and data sourcing through prototyping, validation, deployment, and adoption. Integrate LLM applications with financial‑data platforms, APIs, internal databases, and enterprise systems. Develop context pipelines, evaluation approaches, guardrails, and agentic workflows. Partner closely with bankers, analysts, associates, engineers, security, legal, and other stakeholders. Evaluate opportunities based on feasibility, implementation cost, business value, risk, and expected ROI. Monitor adoption, usage, performance, time savings, and business outcomes for deployed solutions. Role Requirements Approximately 1–4 years of experience in Investment Banking, corporate finance, M&A advisory, capital markets, equity research, or a closely adjacent financial‑services environment. Strong working knowledge of Investment Banking workflows such as pitching, financial modeling, comparable‑company analysis, CIM/OM preparation, diligence, origination, and execution. Hands‑on experience building LLM‑powered applications beyond tutorials or basic prompt engineering. Ability to rapidly prototype across data integration, backend logic, and user‑facing applications. Intermediate proficiency in at least one programming language. Understanding of LLM context design, evaluations, guardrails, and cost/quality tradeoffs. Ability to determine when agentic workflows are appropriate and when simpler solutions are more effective. Strong communication skills with the ability to work across senior business and technical stakeholders. Ability to operate independently in ambiguous, fast‑moving environments. Nice to Have Experience deploying generative AI products into production. Experience with financial‑data platforms such as PitchBook, FactSet, Bloomberg, or SEC EDGAR. Startup, fintech, AI‑product, or entrepreneurial experience. Experience building AI applications within regulated or data‑sensitive environments. Exposure to crypto, digital assets, trading, brokerage, or asset management. #J-18808-Ljbffr Madison-Davis, LLC