Finance Domain Expert (Agentic AI)

Job Description

Finance Expert (AI/LLM and Agentic AI)

Responsibilities

As a Finance Domain Expert, you will play a pivotal role in bridging financial expertise with advanced AI/LLM capabilities. Your responsibilities will include:

• Workflow Definition: Collaborate with AI researchers and engineering teams to define the most common research-based workflows in your domain (e.g., M&A deal analysis in Investment Banking, company valuation in Equity Research, or portfolio construction in Asset Management).
• Evaluation Creation: Design and develop comprehensive evaluation frameworks and test cases to measure workflow completion. This includes specifying inputs, expected outputs, and establishing clear success criteria.
• Capability Assessment: Create assessments that evaluate the LLM’s ability to handle complex financial tasks such as data extraction, financial statement analysis, market trend identification, and risk assessment.
• Data Curation & Annotation: Provide guidance in identifying, curating, and annotating high-quality financial datasets and content to support LLM training and fine-tuning.
• Feedback & Iteration: Partner with product and engineering teams to deliver actionable feedback on LLM performance, recommending improvements to enhance accuracy, reliability, and relevance for financial use cases.

Key Requirements

• Domain Expertise: Minimum 12+ years of professional, hands-on experience in one or more of the following fields:
• Investment Banking: M&A, capital markets, or corporate finance.
• Private Equity: Deal sourcing, due diligence, portfolio management.
• Asset Management: Portfolio management, investment strategy, quantitative analysis.
• Equity Research: Company analysis, financial modeling, report writing.
• Experience Levels: Open to entry-level, mid-level, and executive professionals with proven track records of excellence in their respective domains.
• Analytical Skills: Strong ability to break down complex financial processes into structured, measurable components.
• Communication: Exceptional written and verbal communication skills with the ability to explain complex financial concepts to non-finance stakeholders.
• Technical Acumen: Basic understanding of AI, machine learning, or prior experience collaborating with technical teams is a significant advantage.