AI Product Lead

Job Description

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.

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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.

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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.

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Responsibilities

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• Identify high-friction Investment Banking workflows and translate them into practical AI opportunities.
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• Design and build AI-powered tools supporting workflows such as pitch preparation, comparable-company analysis, diligence, document preparation, client research, and market surveillance.
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• Own the early product lifecycle from opportunity identification and data sourcing through prototyping, validation, deployment, and adoption.
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• Integrate LLM applications with financial-data platforms, APIs, internal databases, and enterprise systems.
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• Develop context pipelines, evaluation approaches, guardrails, and agentic workflows.
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• Partner closely with bankers, analysts, associates, engineers, security, legal, and other stakeholders.
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• Evaluate opportunities based on feasibility, implementation cost, business value, risk, and expected ROI.
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• Monitor adoption, usage, performance, time savings, and business outcomes for deployed solutions.
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Role Requirements

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• 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.
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• Strong working knowledge of Investment Banking workflows such as pitching, financial modeling, comparable-company analysis, CIM/OM preparation, diligence, origination, and execution.
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• Hands-on experience building LLM-powered applications beyond tutorials or basic prompt engineering.
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• Ability to rapidly prototype across data integration, backend logic, and user-facing applications.
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• Intermediate proficiency in at least one programming language.
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• Understanding of LLM context design, evaluations, guardrails, and cost/quality tradeoffs.
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• Ability to determine when agentic workflows are appropriate and when simpler solutions are more effective.
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• Strong communication skills with the ability to work across senior business and technical stakeholders.
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• Ability to operate independently in ambiguous, fast-moving environments.
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• Bachelor’s degree required.
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Nice to Have

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• Experience deploying generative AI products into production.
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• Experience with financial-data platforms such as PitchBook, FactSet, Bloomberg, or SEC EDGAR.
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• Startup, fintech, AI-product, or entrepreneurial experience.
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• Experience building AI applications within regulated or data-sensitive environments.
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• Exposure to crypto, digital assets, trading, brokerage, or asset management.
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