VP AI Business Enablement

The Vice President, AI Business Enablement will help bankers and other employees identify, design, build, and adopt practical uses of artificial intelligence that improve how work gets done across the Firm. Working at the intersection of business analysis, AI technology, workflow design, and user enablement, the Vice President will translate business needs into effective prompts, skills, workflows, agents, and other AI-enabled solutions.

This is a hands-on business enablement role requiring the technical depth to prototype and evaluate AI solutions directly, with a primary focus on business outcomes rather than software engineering. The Vice President will work with bankers, business teams, AI Engineering, Data, Business Technology, IT, Information Security, Legal, and Compliance to deliver practical solutions, develop reusable standards, and help employees use AI safely and effectively.

Key Responsibilities:

· Partner with bankers and staff to understand objectives and pain points; prioritize AI use cases by impact, feasibility, frequency, adoption potential, and effort. Redesign workflows and determine which tasks belong with AI, automation, traditional technology, or people.

· Translate business needs into clear requirements for prompts, skills, workflows, agents, data access, integrations, and supporting technology. Determine when configuration is sufficient and when engineering or data support is required.

· Develop and refine prompts, reusable skills, custom assistants, workflow instructions, and lightweight automations; rapidly prototype solutions using approved enterprise AI platforms and partner with technical teams on more complex builds.

· Evaluate prompts and workflows for accuracy, clarity, reliability, efficiency, maintainability, and appropriate context use. Address excessive token use, duplicated instructions, unnecessary complexity, and brittle workflows.

· Develop test cases, evaluation criteria, and practical documentation standards; compare alternative prompts, models, tools, and workflow designs. Monitor deployed solutions and refine them based on usage, feedback, quality, cost, and changing model capabilities.

· Develop and deliver practical training and individual or small-group working sessions focused on real business tasks. Teach users to structure prompts, provide context, validate results, and recognize when AI should or should not be used.

· Create examples, templates, reference materials, and reusable skills; coach advanced users and AI champions to support adoption and increase employee proficiency and self-sufficiency.

· Help users mature promising prototypes into reusable Firm capabilities and maintain a curated library of approved solutions. Review user-created techniques for applicability, quality, maintainability, security, and compliance; standardize and share effective solutions and reduce duplication.

· Ensure solutions meet Firm confidentiality, security, data-access, compliance, and responsible-use requirements. Guide sensitive-information handling and human review; partner with control and technical teams and escalate solutions requiring additional assessment.

· Capture evolving best practices and measure business adoption and outcomes, including workflows improved, time saved, repeat usage, output quality, user satisfaction, employee proficiency, and user-created solutions standardized for broader reuse.

Required Skills:

· Strong business analysis, requirements gathering, process mapping, and workflow-design skills, with genuine curiosity about how bankers and staff work and an ability to translate between business and technical teams.

· Advanced practical experience with enterprise generative AI platforms and demonstrated ability to design and optimize complex prompts, reusable instructions, custom assistants, skills, agents, or lightweight automations.

· Understanding of context windows, retrieval, grounding, hallucination, structured outputs, tool use, agents, model selection, and evaluation; ability to test AI outputs systematically rather than rely on plausibility.

· Familiarity with APIs, connectors, structured and unstructured data, enterprise search, and retrieval-augmented generation concepts.

· Comfort working with Excel, PowerPoint, document workflows, customer relationship management systems, collaboration platforms, and other business tools.

· Excellent written and verbal communication, presentation, facilitation, and training skills; ability to work effectively with senior bankers and executives as well as junior bankers, assistants, and corporate staff.

· A practical builder and teacher mindset, focused on useful, maintainable solutions and helping users become more capable and self-sufficient.

· Sound judgment on experimentation, sensitive information, and escalation; intellectual curiosity and commitment to adapting techniques as AI models and platforms evolve.

Nice to Haves:

· Basic familiarity with SQL, Python, scripting, or other technical tools is strongly preferred; deep software engineering expertise is not required.

· Financial-services or other professional-services experience is strongly preferred, particularly in investment banking, capital markets, consulting, legal, or other knowledge-intensive environments.

Education & Experience:

· Bachelor’s degree or equivalent professional experience.

· Approximately 5–10 years of experience in business analysis, product management, technology consulting, workflow automation, enterprise applications, data and analytics, or a related field.

· Meaningful hands-on experience applying generative AI to real business workflows and translating loosely defined business problems into practical technology solutions.

· Demonstrated experience working directly with business users through discovery, design, implementation, training, and adoption.