AI Governance Team, AI Risk and Operations

AI Governance Team, AI Risk and Operations

We are the better way to work in finance. As private equity's value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation.

If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment.

Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark.

We are seeking a Vice President, AI Risk and Operations on our AI Governance Team who will play a critical role in maturing and scaling Accordion's enterprise-wide AI Governance risk and operations program. In this role, you will serve as an internal governance practitioner and cross-functional advisor, embedding AI governance policies, procedures, and controls across our operating model for internal AI solutions — with the expectation that this scope will evolve to include client-facing engagements over time.

Drawing on your experience with AI policy, frameworks, and risk program design, you will translate complex governance requirements into actionable, scalable implementation systems. This position requires seamlessly bridging the gap between cutting-edge AI development and responsible governance, partnering with senior stakeholders across Practices, Technology, Legal, and Emerging Technology to enabling trusted use and development of AI.

This position can be based in our New York City or Chicago offices and is a hybrid role with the flexibility to work remotely 2 days a week. Ideal candidates should be local to the desired location.

This position is not eligible for immigration sponsorship.

Governance & Frameworks

• Enhance the enterprise AI Risk Management Framework, including AI use case and supply chain inventory management, use case risk classification taxonomies, and risk-tiering mechanisms aligned to internal standards and emerging regulatory expectations
• Design and operationalize scalable, end-to-end governance processes across the AI lifecycle
• Build and maintain AI governance playbooks, risk appetite frameworks, and responsible AI standards
• Identify opportunities to strengthen controls and oversight through process automation, tooling improvements, and governance workflow optimization

Cross-Functional Collaboration

• Partner with Legal, Technology, and Consulting Practice Groups to embed explainability, bias mitigation, and ethical AI principles directly into use case development and delivery workflows
• Manage the firm's AI Governance obligations and processes end-to-end, including supporting AI and related vendor management supply chain
• Coordinate with Legal teams to ensure AI systems meet applicable jurisdictional and regulatory requirements, including proactive engagement on evolving global AI legislation
• Facilitate stakeholder working groups, cross-functional governance forums, and executive communications on AI risk priorities, testing outcomes, and documentation requirements
• Maintain the internal AI risk register and escalate issues through appropriate governance channels
• Liaise with Technology and Practices to ensure data lineage and quality standards are met for AI solutions

Monitoring & Oversight

• Establish, track, and report on key risk indicators (KRIs) for AI systems in partnership with the Responsible AI Data Scientist and AI Governance Lead, across internal and client-facing AI solutions and products
• Monitor alignment with global AI regulatory frameworks (e.g., EU AI Act, NIST AI RMF) and support responses to regulatory inquiries, audits, or reviews
• Evaluate risks associated with third-party and vendor AI solutions across the full sourcing lifecycle — including procurement, onboarding, integration, and ongoing performance oversight — and identify operational guardrails and controls
• Assess design and operating effectiveness of AI controls against…