Finance Systems AI Transformation Lead

We are looking for a Finance Systems AI Transformation Lead to join a Long-term Contract opportunity based in Menlo Park, California. This role sits at the intersection of finance and artificial intelligence, with a focus on improving planning, reporting, and close-related activities through practical automation. You will partner with finance and systems teams to turn complex operational processes into scalable AI-enabled solutions that improve accuracy, speed, and decision support.

Responsibilities:

• Design and implement AI-driven solutions that simplify core finance activities such as forecasting support, variance review, close coordination, allocation workflows, and workforce planning analysis.
• Build intelligent, multi-step automations that interpret financial information, interact with connected tools, and produce traceable outputs suitable for business use.
• Develop integrations between AI applications and enterprise finance platforms, planning systems, and data environments to support reliable information exchange.
• Create data retrieval pipelines that connect large language model capabilities with structured finance data, including reporting histories, ledger structures, cost center details, and planning records.
• Establish controls and validation methods that allow automated solutions to read, verify, and update finance-related data with consistency and audit readiness.
• Define and execute evaluation approaches to measure solution quality, including output accuracy, stability, explainability, and risk of failure in finance use cases.
• Monitor production performance, investigate issues, and refine workflows based on user feedback, testing results, and observed system behavior.
• Partner closely with finance stakeholders, financial systems teams, and technical counterparts to convert manual finance processes into scalable AI-supported operations.
• Lead user acceptance testing activities and confirm that delivered solutions meet finance, controllership, and audit expectations before broader rollout.