Head of AI Finance and Automation Deployment

The Head of Finance Systems and Automation or Director of AI Finance Transformation leads the strategic implementation of artificial intelligence and machine learning across enterprise financial workflows. This role merges deep finance domain knowledge with technical fluency to automate the financial close, streamline FP&A, and drive measurable ROI.

We are seeking an innovative finance leader to own the strategy, implementation, and continuous improvement of our finance technology stack. You will be a builder-first executive who blends enterprise architecture with AI automation, eliminating manual workflows, tightening our financial data fabric, and enabling the finance team to move with speed and scale.

• AI & Automation Strategy: Design and execute a multi-year roadmap to modernize Controllership, FP&A, and revenue cycles using AI and machine learning.
• System Deployment: Spearhead the end-to-end lifecycle of AI deployment—from use-case identification and vendor selection to model tuning, integration, and performance tracking.
• Compute & Infrastructure ROI: Partner with Engineering and Infrastructure teams to forecast compute demand, manage margin outcomes, and optimize the costs of capital-intensive AI infrastructure.
• Change Management: Lead cross-functional collaboration with IT, compliance, and business units to drive high adoption rates of AI agents while ensuring strong financial controls and risk management.
• Performance Evaluation: Establish measurement frameworks to evaluate AI's ROI, tracking both direct financial gains and indirect benefits such as speed, accuracy, and fraud reduction.

• Experience: 8+ years in financial systems, corporate finance, or financial transformation, with at least 3+ years directly leading AI/automation deployments.
• Technical Acumen: Strong familiarity with cloud financial operations (Fin Ops), AI integration, API utilization, and hands‑on capability with querying and data manipulation (e.g., SQL, Python).
• Leadership: Proven ability to bridge the gap between technical teams (engineers, data scientists) and business stakeholders.