Quick summary
- Work type
- On-site
- Location
- Chicago, ILNew York, NYSeattle, WASan Francisco, CA
- Salary
- $147,200–$220,800 / yr
- Posted
- 2 days ago
- Freshness
- Confirmed live today
- Nearby
- 99+ roles within 25 mi
Employer
About Stripe
Stripe is a financial infrastructure platform for internet businesses, providing payment processing, billing, fraud prevention, and banking-as-a-service APIs to businesses of all sizes globally. Industry: Payments Infrastructure & Financial Technology
Stripe currently has 150 open roles on FindRole.
Listed pay typically runs $199,400–$295,300 across 148 roles with salary data.
Most-posted roles
- Software Engineer 19
- Product Manager 13
- Account Executive 10
- Client Platform Security Engineer 6
- Engineering Manager 6
At a glance
TL;DR · AI Solutions Developer
As an AI Solutions Developer on the Finance Operational Excellence team, you will function as a solution developer, data architect, and workflow designer to redefine finance processes through applied AI. You will work alongside Finance subject matter experts to identify high-impact opportunities, automate manual workflows, and build AI agents that provide reliable, long-term solutions for the organization. Your daily work involves building and operationalizing agents, optimizing data pipelines, creating knowledge layers, and developing validation patterns to ensure accuracy. You will utilize SQL for complex data extraction and transformation while leveraging low-code tools, scripting, and version control practices. The role focuses on solving technical and business problems within finance operations by translating requirements into practical automation, providing training and documentation to enable team ownership, and collaborating with Engineering to integrate custom tools where necessary.
Skills
What you'll do
- Diagnose finance workflows to identify high-leverage opportunities for automation and AI integration.
- Build and operationalize end-to-end AI agents for specific finance use cases from prototype to handoff.
- Write and optimize complex SQL queries to ensure data outputs are accurate, reliable, and explainable.
- Design reusable knowledge layers, validation patterns, and data-quality frameworks to improve agent accuracy.
- Develop custom tools and integrations in collaboration with Engineering when platform limitations are encountered.
- Create documentation, runbooks, and training materials to enable finance teams to maintain solutions independently.
- Establish monitoring and observability for deployed agents, including metrics and incident-response processes.
- Measure adoption and impact to turn successful implementations into standard playbooks for the broader organization.
What we're looking for
- 5+ years of experience in data analytics, technical operations, business intelligence, automation, solutions delivery, or a related field.
- Hands-on experience building AI-enabled tools, agents, automations, or workflows that changed a real business process.
- Strong SQL proficiency including complex queries using CTEs, window functions, and joins for data analysis and transformation.
- A track record of independently scoping and delivering technical solutions for process improvement from problem definition through adoption.
- Strong analytical and investigative skills to identify root causes, debug complex data problems, and resolve inconsistencies.
- Strong written and verbal communication skills to explain technical concepts to non-technical audiences.
- Experience teaching, coaching, enabling users, or transferring ownership of a solution through documentation and training.
- 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.
- Domain experience in Finance Operations, FP&A, Accounting, Treasury, Tax, or Payments (preferred).
- Familiarity with Python, Databricks, ETL/ELT processes, data pipelines, and data-quality controls (preferred).
- Experience with Model Context Protocol or other extensibility frameworks (preferred).
- Experience navigating financial systems and understanding how data flows through accounting, reporting, reconciliation, forecasting, or payments (preferred).
- Experience with change management, organizational transformation, or large-scale enablement programs (preferred).
- Experience building internal tools, templates, components, or playbooks adopted beyond the original team (preferred).
- Experience working in a high-growth technology company with rapidly evolving processes and tools (preferred).