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Stripe

AI Solutions Program Manager, Finance

Stripe is hiring an AI Solutions Program Manager, Finance for a remote role open to applicants in United States. Level rates it ; you can apply on Stripe.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this finance role: the daily work is on AI products, without building the model.
  • This is listed as a remote role.
  • The posting mentions Databricks, Internal Platforms and AI agents among its tools and skills.
  • Level classes it as a senior role.
  • Stripe has 771 other open roles on Level.

AI in this role

Drive finance transformation and operational excellence by building applied AI solutions, agents, and automated workflows for finance teams.

DatabricksInternal Platforms
ai-agentsprocess-automationworkflow-designapplied-aidata-architectureagent-building

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, data, and control requirements into practical AI and automation solutions.
  • Build and operationalize AI agents for Finance use cases, delivering end-to-end solutions from prototype through validation, monitoring, documentation, and handoff.
  • Write and optimize SQL for data extraction, transformation, calculation, and validation, ensuring Finance-facing outputs are accurate, explainable, and reliable.
  • Design reusable knowledge layers, evaluation methods, validation patterns, data-quality frameworks, and components that improve agent accuracy and accelerate future use cases.
  • Identify agentic limitations and new possibilities; determine when to use existing capabilities, develop an alternative approach, or partner with Engineering to scope and test custom tools and integrations, including tools using Model Context Protocol where appropriate.
  • Build alongside users, gather feedback through real deliverables, and iterate until the solution fits the workflow and earns user trust.
  • Enable long-term ownership through clear SOPs, runbooks, training, and self-service tooling; coach Finance teams to operate, maintain, and evolve what has been built.
  • Establish monitoring and observability for deployed agents, including metrics, alerting, and incident-response processes that support reliable operation.
  • Diagnose technical and data issues, resolve problems independently where possible, and collaborate with Engineering when solutions require deeper platform changes.
  • Measure adoption and impact, share lessons and wins, and turn successful implementations into standards, components, and playbooks for the broader Finance AI portfolio.

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

  • 5+ years of experience in data analytics, technical operations, business intelligence, automation, solutions delivery, or a related field.
  • Of which, 2+ years of experience in program management, working directly alongside business leaders to develop and execute process transformation programs
  • Hands-on experience building AI-enabled tools, agents, automations, or workflows that changed a real business process—not solely using AI as a conversational tool,
  • Strong SQL proficiency, including experience writing complex queries using CTEs, window functions, and joins for data analysis, transformation, or pipeline logic.
  • A track record of independently scoping and delivering technical solutions for process improvement, demonstrating ownership from problem definition through adoption.
  • Strong analytical and investigative skills, including the 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.

How we rate this

AI Solutions Program Manager, Finance at Stripe rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsProcess AutomationWorkflow DesignApplied AIData ArchitectureAgent BuildingDatabricksInternal Platforms

Also common in finance jobs at this level

Pay

Typical finance job
$105k

This posting doesn't list pay. Use the typical finance figure when pay comes up. See finance jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a project where process automation was part of your work. What did you do?
  3. Tell me about a project where workflow design was part of your work. What did you do?
  4. Tell me about a project where applied ai was part of your work. What did you do?
  5. Tell me about a project where data architecture was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, Process Automation, Workflow Design, Applied AI, and Data Architecture. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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