AI Solutions Program Manager, Finance

The posting, as Stripe wrote it

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

You'll be joining the Finance Operational Excellence team, reporting to the Head of Finance Operational Excellence. We are finance transformation and AI experts working side-by-side with Finance, Product, and Engineering teams to redefine processes and build the finance organization of the future. This is an opportunity for someone who enjoys working across disciplines: part solution developer, part data architect, part workflow designer, and part coach. You’ll have room to shape how applied AI is built and scaled both from a technical and end-user perspective.

What you’ll do

You'll work side-by-side with Finance subject matter experts to understand how work gets done, identify the highest impact opportunities, and partner with domain teams to chart a transformation plan which balances future ambitions with rapid impact. You'll work independently to automate manual processes, design and build agents and required data solutions using internal platforms, and enable Finance teams to maintain these solutions long-term.

You’ll build with your partner teams, not simply deliver solutions to them. You’ll help colleagues move from a manual workflow, to a first AI-enabled win, to a reliable solution they can confidently operate and improve themselves. Success means the workflow stays transformed after the initial build, the team trusts the output, and the people closest to the process can own what comes next.

You’ll favor learning through building. When possible, you’ll put a useful prototype in front of a Finance user, test it against a real deliverable, and improve it quickly rather than spend weeks describing a theoretical future state. When you encounter platform limitations—which you will—you’ll find creative, supportable approaches, collaborate with Engineering to scope and test custom tools, and escalate strategically when needed.

This role requires a blend of process automation, data operations, technical problem-solving, and stakeholder enablement. You'll spend your time building agents, optimizing data pipelines that feed them, creating knowledge layers that make them more accurate, and training Finance teams to use and maintain them. Success means Finance teams can independently run agents you've built while you provide light support and focus on the next automation opportunity.

Responsibilities

• Embed with Finance teams to diagnose workflows, identify high-leverage opportunities, and translate business,

[…]
ability to identify root causes, debug complex data problems, and resolve inconsistencies.

• Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences and work effectively with domain experts and Engineering partners.
• Experience teaching, coaching, enabling users, or transferring ownership of a solution through documentation, training, or self-service tools.
• Working knowledge of development practices such as version control, testing, code review, and iterative delivery.
• Experience using low-code tools, scripting, workflow automation, AI-assisted development, or custom integrations, paired with curiosity and the ability to learn evolving technologies.

You will also likely have (not required)

• Domain experience in Finance Operations, Financial Planning & Analysis (FP&A), Accounting, Treasury, Tax, Payments, or other areas.
• Familiarity with modern data tools and practices, such as Python, Databricks, ETL/ELT processes, data pipelines, and data-quality controls.
• Experience with Model Context Protocol or another extensibility or integration framework.
• Experience navigating financial systems and understanding how data flows through accounting, reporting, reconciliation, forecasting, or payments processes.
• Experience with change management, organizational transformation, or large-scale enablement programs.
• Experience building internal tools, templates, components, or playbooks that were adopted beyond the original team or use case.
• Experience working in a high-growth technology company with rapidly evolving processes and tools.

Note on technical depth : This role involves working at the intersection of no-code AI tools and custom development. While software engineering expertise is not required, you should be comfortable applying technical concepts, collaborating closely with Engineering teams, and using AI-assisted development tools to extend platform capabilities when needed.