Senior Manager, Finance AI Transformation

We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry.

This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.

Everpure's Data and Analytics (DnA) organization is seeking a Senior Manager, Finance AI Transformation to help Finance run AI, automation, analytics, and data as a core operating strategy rather than a side project. This role combines deep finance expertise with hands‑on AI and transformation leadership to drive meaningful change across the Office of the CFO.

You will serve as the business‑facing strategy and adoption lead for DnA's AI Factory for Finance, helping identify high‑value opportunities, build and validate solutions, and scale successful capabilities across Finance. Working closely with leaders across Accounting, Revenue, Order Management, and GTM Finance, you will help translate trusted data and AI capabilities into measurable improvements in productivity, controls, and executive decision‑making.

This is a highly collaborative role that partners across Finance, DnA, and IT to bring AI‑enabled solutions to life while establishing the governance, controls, and adoption frameworks necessary for long‑term success.

• Partner with Finance teams to identify high‑value AI and automation opportunities and redesign underlying processes to enable AI‑driven workflows.
• Prioritize opportunities, validate concepts through focused pilots, and scale successful solutions with measurable business outcomes and adoption plans.
• Act as the bridge between Finance, DnA, and IT/Business Systems by translating business requirements into process, data, system, and control requirements.
• Help design trusted finance data products, semantic layers, workflows, and AI‑enabled capabilities that reduce manual effort and improve decision‑making.
• Build the operating cadence for transformation delivery, including intake processes, business cases, prioritization, milestones, risk management, stakeholder communications, adoption metrics, and benefits realization.
• Drive adoption of Finance AI capabilities through user acceptance testing, training, launch communications, operating procedures, and ongoing feedback loops.
• Define and track value realization metrics including cycle‑time reduction, productivity improvements, adoption rates, control enhancements, quality gains, and stakeholder satisfaction.
• Partner with Finance leadership to ensure AI and automation initiatives align with business priorities and operational objectives.

We are primarily an in‑office environment and therefore, you will be expected to work from the Santa Clara, CA office in compliance with Everpure's policies, unless you are on PTO, work travel, or other approved leave.

• 8+ years of experience in finance transformation, accounting, revenue or GTM finance, finance operations, consulting, business systems, data and analytics, or related functions.
• Strong understanding of core finance and accounting processes, including close, general ledger, revenue recognition, Quote‑to‑Cash, Order‑to‑Cash, Record‑to‑Report, controls, and related finance operations.
• Demonstrated experience evaluating, piloting, or deploying AI‑enabled capabilities such as Generative AI, agentic AI workflows, machine learning, predictive analytics, intelligent automation, or workflow solutions within Finance or related functions.
• Hands‑on experience experimenting with emerging AI technologies and building practical prototypes using modern AI tools.
• Experience with finance systems and platforms including ERP, CRM, CPQ, billing, close and reconciliation tools, cloud data platforms, and business intelligence solutions.
• Ability to define requirements for finance data products, semantic layers, dashboards, and AI‑enabled capabilities.
• Strong understanding of responsible AI principles, data governance, access controls, auditability, model risk, privacy, SOX considerations, and…