AI Business Engineer - Investment Banking Experience

Job Description Summary

The AI Business Engineer supports the adoption and effective use of generative AI across the Investment Bank and Capital Markets & Advisory functions by designing, building, and improving AI-powered solutions across banker workflows through custom GPTs and prompts and emerging agent-based tools. This role blends technical curiosity with practical application and deep business knowledge, contributing to prompt engineering, solution development, and user support while maintaining best practices and documentation. The individual partners with stakeholders to deliver training, troubleshoot issues, and enhance user experience, while also evaluating technology trends and vendors to drive innovation and business value.

Job Description

Responsibilities

• This role will directly support the Investment Bank and Capital Markets & Advisory function and its use of generative AI, including GPTs and future agent-based solutions.
• Support the design, development, testing, and ongoing improvement of GPTs, AI-powered workflows, and (over time) agent-based solutions
• Assist with prompt engineering, prompt optimization, and documentation of effective prompting patterns and use cases
• Help maintain standards, best practices, and internal documentation related to AI tools, automation, and innovation platforms
• Provide hands-on support to internal users, helping troubleshoot issues and improve overall user experience with AI-enabled tools
• Design and deliver role-specific training to finance professionals
• Contribute to short- and long-term innovation roadmaps through research, analysis, and execution support
• Analyze technology trends, tools, and vendor offerings to identify opportunities for experimentation or business value
• Generate insights and recommendations that help improve internal technology offerings and identify areas for growth
• Assist with data analysis and reporting related to innovation initiatives, pilots, and outcomes
• Create and maintain presentation materials, including PowerPoint decks, charts, and visuals for leadership and stakeholder updates
• Facilitate meetings with internal teams and external vendors; capture notes, actions, and follow-ups
• Draft concise summaries, reports, or briefing materials on technology topics, vendors, or pilot results Contribute ideas and perspectives to brainstorming sessions and innovation ideation efforts

Skills

• The ideal candidate is curious, technically inclined, and excited about applying emerging technologies—especially generative AI—to real business problems.
• 1–4 years of experience in technology, software, digital innovation, or related roles (financial services experience a plus, but not required)
• Strong interest in generative AI, automation, and modern software platforms (e.g., LLMs, GPTs, agents, APIs, low-code/no-code tools)
• Working knowledge of Python and SQL to support data exploration, workflow automation, and AI prototype development; ability to read, modify, and apply scripts with guidance from engineering partners — deep software engineering experience not required
• Proficiency in data analysis using advanced Excel (e.g., pivot tables, XLOOKUP/VLOOKUP, conditional logic) to support reporting, pilot measurement, and business case development
• Experience supporting or managing vendors, including coordination around licenses, contracts, or service delivery
• Working knowledge of project and program management fundamentals
• Ability to operate effectively in a fast-paced, evolving environment and adapt quickly as priorities and technologies change
• Demonstrated ability to think creatively and encourage new approaches or ways of working
• Strong written communication skills, with the ability to explain technical or complex concepts clearly and concisely
• Comfortable creating and interpreting charts, diagrams, tables, and other data visualizations
• Genuine interest in following technology trends, innovation research, and emerging tools
• Excellent verbal communication and collaboration skills
• High attention to detail with the ability to manage multiple workstreams simultaneously
• Team-oriented mindset with the ability to work across technical and non-technical stakeholders

What success looks like

• High-value AI use cases are moved from idea to pilot to scaled adoption.
• Solutions are deployed with clear testing, documentation, and governance controls.
• Banker adoption increases and workflo…