AI Operations Sr. Manager

About the role

AI Enablement & Team Training
Serve as the organization's go-to expert on applied AI for finance, accounting, and operations.
Own the rollout of Claude Essentials across the team — deliver intro and advanced workflow training, office hours, and certification of core skills.
Establish responsible-AI guardrails, review practices, and documentation so outputs are accurate, auditable, and control-compliant.

Workflow Automation
Identify high-value automation opportunities and build Claude and other AI-native workflows across close, AP, reconciliations, reporting, and audit support.
Reduce manual, rules-based effort while preserving data integrity and internal controls.

Operations & Kiosk Finance (Expanding Scope)
Extend AI-native workflows into kiosk cash reconciliation — automate cash reconciliation across a ~7,300-kiosk fleet (growing to ~8,000), surfacing variances and exceptions for review.
Support inventory management — device and parts tracking, valuation, and shrink/variance analysis across the network.
Streamline fixed-asset and kiosk-fleet accounting — additions, transfers, retirements, and depreciation across a large, distributed asset base.

Modeling & Forecasting
Support and enhance financial and operational modeling and forecasting with AI — scenario analysis, variance decomposition, and driver-based projections.
Improve the speed and quality of management reporting and analytics used by leadership.

Broader Finance & Operations Impact
Act as an internal consultant to Accounting, FP&A, Treasury, Tax, and Operations on where AI can add measurable value.
Track and report adoption, time savings, and ROI from deployed workflows.

Requirements

• 5+ years in data/analytics, automation, or finance-technology roles with hands-on delivery.
• Demonstrated expertise with LLM / generative-AI tools (Claude or equivalent), including prompt engineering and workflow design.
• Strong SQL and experience with Snowflake, Oracle, or comparable enterprise data platforms.
• Working knowledge of accounting and finance processes (close, reporting, AP, forecasting).
• Proven ability to teach and up-skill non-technical business users.
• Preferred Programming/scripting (Python) and experience with automation frameworks or APIs.
• Experience building forecasting/modeling solutions or BI dashboards.
• Exposure to retail/operations data — cash reconciliation, inventory, or asset-fleet management — a strong plus.
• Background bridging finance and technology; understanding of internal controls, data governance, and audit requirements.