Subject Matter Expert, Investment Banking

OpenAI•San Francisco, CA

10d•$185,000 - $205,000•Hybrid

About The Position

OpenAI is building AI systems that can help professionals perform complex, high-value work with greater speed, rigor, and creativity. Investment banking is one of the most demanding environments for knowledge work: bankers must synthesize fragmented information, exercise judgment under pressure, and produce precise, defensible models, analyses, and client materials. Our team works across Research, Product, Engineering, and Go-to-Market to make OpenAI's models genuinely useful for these workflows. We translate real professional work into product requirements, evaluations, training signals, and repeatable customer solutions. We care not only whether a model can generate an answer, but whether it can deliver accurate, defensible work that experienced bankers can trust and use. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. We are looking for a Subject Matter Expert in Investment Banking to help define what excellent AI-assisted banking work looks like and turn that standard into better models and products. You will bring deep, current knowledge of how investment banking work is actually performed, including company and industry research, financial analysis and modeling, valuation, diligence, transaction execution, and the creation and review of client materials. You will use that expertise to design realistic tasks and evaluations, create and assess high-quality reference work, diagnose model failures, and help our technical teams improve model behavior and product experiences. This is a hands-on individual-contributor role for someone who enjoys both doing the work and explaining what makes it good. You should be comfortable moving between an Excel model, a presentation, a source document, an evaluation rubric, a product prototype, and a conversation with researchers or customers. You will help us distinguish outputs that merely look plausible from work that is accurate, traceable, internally consistent, and ready for serious professional use.

Requirements

Have 2+ years of investment banking experience, including live transaction execution and the production of high-quality analyses, financial models, and client materials. Demonstrated ability and judgment matter more than title or tenure.
Have strong command of core banking workflows across M&A, capital raising, strategic advisory, or a closely related product or coverage area.
Can build and review financial analyses in Excel and produce polished PowerPoint materials, with a sharp eye for errors, weak assumptions, unsupported claims, inconsistent numbers, and poor presentation.
Understand how work and judgment evolve from junior analyst through director, and can identify where AI should automate execution, support decision-making, or remain subject to human review.
Exercise excellent analytical judgment and can assess whether an approach is appropriate, evidence is sufficient, and an output would withstand senior review.
Can translate expert intuition into clear standards, actionable feedback, rubrics, and guidance that others and evaluation systems can apply consistently.
Thrive in ambiguous, zero-to-one environments and are willing to create the first version of a task, model, deck, rubric, workflow prototype, or playbook.
Are curious about AI, comfortable collaborating with technical and non-technical stakeholders, and able to apply sound judgment around confidentiality, data entitlements, governance, regulation, and reputational risk.

Nice To Haves

Experience across multiple banking products, industry coverage groups, geographies, or transaction types, or in adjacent fields such as private equity, corporate development, equity research, private credit, leveraged finance, or restructuring.
A track record of improving financial workflows through automation, templates, knowledge systems, data tools, process redesign, or new technology.
Familiarity with evaluation design, quality assurance, benchmarking, data annotation, prompt design, or testing AI-enabled financial tools.

Responsibilities

Define the quality bar for AI-assisted investment banking work across research, financial analysis, valuation, modeling, diligence, transaction execution, and client materials.
Translate real banking workflows into challenging, representative evaluation tasks with realistic inputs, constraints, deliverables, and success criteria.
Create and refine banker-grade reference artifacts, including financial models, valuation analyses, diligence materials, screening outputs, pitch books, committee materials, and transaction documents.
Develop rigorous rubrics and grading methods that assess financial correctness, analytical judgment, source quality, traceability, internal consistency, presentation quality, and practical usefulness.
Evaluate model outputs and end-to-end agent workflows, identify recurring failure modes, and translate findings into actionable feedback for Research, Engineering, and Product.
Partner with researchers and engineers on evals, graders, datasets, human-review processes, tools, and product integrations that improve model performance on financial work.
Work closely with product teams to identify the highest-value opportunities for AI in investment banking, prototype new workflows using OpenAI tools, and assess whether early experiences meet the needs of real users.
Engage with customers, design partners, and domain reviewers to understand real-world standards and constraints, support testing and adoption, codify domain knowledge, and ensure responsible financial-services deployment.