AI Solutions Program Manager, Finance
for section headings: e.g., About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we must only include sections when posting has real specific content. We need to map content to these headings. The instructions: Use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should use those exact headings? Probably yes: we should use those headings where appropriate. The posting has sections like "About The Team", "What you’ll do", "Responsibilities", "Who you are", "Minimum Requirements", "You Will Also Likely Have (not Required)", "Note on technical depth", "In-office expectations", "Pay and benefits". We need to map to the allowed headings.
We have to avoid repeating job title as heading (not present). No Job ID.
We need to include - for any list of duties/requirements/benefits, and
for prose.
We must preserve all substantive information, not invent or summarize away detail. Remove boilerplate etc.
We must include a section ONLY when posting has real specific content for it — never emit a heading followed by filler/placeholder text.
Thus we need to decide which of the allowed headings we have content for:
- About the role: could map to "What you’ll do" or "About The Team"? Probably "About the role" corresponds to description of role. We have "What you’ll do" and "About The Team". Could combine? But we need to follow headings exactly? Might be okay to use "About the role" heading and put content from "What you’ll do" and maybe "About The Team". However we must not invent content; we can put the prose there.
- Responsibilities: we have a "Responsibilities" section with bullet points.
- Requirements: we have "Minimum Requirements" and also "You Will Also Likely Have (not Required)" which could be qualifications/skills. Could map "Requirements" to minimum requirements, "Qualifications" to preferred qualifications, "Skills" maybe to technical skills? But we have to avoid filler. We have content for minimum requirements and preferred qualifications. So we can have sections Requirements (minimum) and Qualifications (preferred). Skills maybe not needed if no explicit skills list separate; but we could put skills under Qualifications? Might be okay to omit Skills if no specific content.
- Benefits: we have "Pay and benefits" includes salary range and benefits list. So we can have Benefits section (maybe also Pay). But we have separate Pay and Benefits headings allowed. We could put Pay under Pay heading and Benefits under Benefits heading. However the posting lumps them together. We could split: Pay: salary range; Benefits: equity, bonus, 401k, medical etc. That's okay as we are not inventing; we just split the content.
- Schedule: we have "In-office expectations" which describes schedule expectations. So we can use Schedule heading for that.
Thus we will output sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule. Possibly also Skills? Not needed.
We must not include empty sections.
Now we need to format: For each section,
Heading
then content. For lists, use - ... etc. For prose,
.
We need to preserve all substantive information. Let's extract content.
First, "About the role": combine "About The Team" and "What you’ll do". Let's capture both paragraphs.
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: multiple paragraphs. Let's capture them as prose.
We'll combine into maybe multiple
under About the role.
Now Responsibilities: list of bullet points. Each bullet starts with a bold verb? We'll extract each line.
Responsibilities bullet list:
- 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.
Now Requirements (minimum): list.
Minimum Requirements bullet list:
- 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.
Now Qualifications (preferred): "You Will Also Likely Have (not Required)" list.
- 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.
Also note "Note on technical depth:" paragraph. That could be part of Qualifications or maybe a separate note. We could include it under Qualifications as additional prose. But we must not invent headings. Could add a
under Qualifications after list.
Now Benefits: list from "Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends."
Also maybe mention "Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process." That's more about Pay.
Pay: "The annual US base salary range for this role is $147,200 - $220,800. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process."
We need to keep that.
Now Schedule: In-office expectations paragraph.
Now we need to ensure we don't include boilerplate like "We look forward to hearing from you." etc. That's at end after Pay and benefits. Also "At Stripe, we're looking for people with passion, grit, and integrity..." etc. That's boilerplate; we should remove. Also "Please find our California applicant personal information notice here." Remove.
Also "We look forward to hearing from you." Remove.
Now we need to output only HTML fragment.
Let's craft.
Structure:
About the role
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.
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
- for any list of duties/requirements/benefits, and
for prose. We must preserve all substantive information, not invent or summarize away detail. Remove boilerplate etc. We must include a section ONLY when posting has real specific content for it — never emit a heading followed by filler/placeholder text. Thus we need to decide which of the allowed headings we have content for: - About the role: could map to "What you’ll do" or "About The Team"? Probably "About the role" corresponds to description of role. We have "What you’ll do" and "About The Team". Could combine? But we need to follow headings exactly? Might be okay to use "About the role" heading and put content from "What you’ll do" and maybe "About The Team". However we must not invent content; we can put the prose there. - Responsibilities: we have a "Responsibilities" section with bullet points. - Requirements: we have "Minimum Requirements" and also "You Will Also Likely Have (not Required)" which could be qualifications/skills. Could map "Requirements" to minimum requirements, "Qualifications" to preferred qualifications, "Skills" maybe to technical skills? But we have to avoid filler. We have content for minimum requirements and preferred qualifications. So we can have sections Requirements (minimum) and Qualifications (preferred). Skills maybe not needed if no explicit skills list separate; but we could put skills under Qualifications? Might be okay to omit Skills if no specific content. - Benefits: we have "Pay and benefits" includes salary range and benefits list. So we can have Benefits section (maybe also Pay). But we have separate Pay and Benefits headings allowed. We could put Pay under Pay heading and Benefits under Benefits heading. However the posting lumps them together. We could split: Pay: salary range; Benefits: equity, bonus, 401k, medical etc. That's okay as we are not inventing; we just split the content. - Schedule: we have "In-office expectations" which describes schedule expectations. So we can use Schedule heading for that. Thus we will output sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule. Possibly also Skills? Not needed. We must not include empty sections. Now we need to format: For each section,
Heading
then content. For lists, use- ... etc. For prose,
. We need to preserve all substantive information. Let's extract content. First, "About the role": combine "About The Team" and "What you’ll do". Let's capture both paragraphs. 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: multiple paragraphs. Let's capture them as prose. We'll combine into maybe multiple
under About the role. Now Responsibilities: list of bullet points. Each bullet starts with a bold verb? We'll extract each line. Responsibilities bullet list: - 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. Now Requirements (minimum): list. Minimum Requirements bullet list: - 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. Now Qualifications (preferred): "You Will Also Likely Have (not Required)" list. - 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. Also note "Note on technical depth:" paragraph. That could be part of Qualifications or maybe a separate note. We could include it under Qualifications as additional prose. But we must not invent headings. Could add a
under Qualifications after list. Now Benefits: list from "Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends." Also maybe mention "Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process." That's more about Pay. Pay: "The annual US base salary range for this role is $147,200 - $220,800. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process." We need to keep that. Now Schedule: In-office expectations paragraph. Now we need to ensure we don't include boilerplate like "We look forward to hearing from you." etc. That's at end after Pay and benefits. Also "At Stripe, we're looking for people with passion, grit, and integrity..." etc. That's boilerplate; we should remove. Also "Please find our California applicant personal information notice here." Remove. Also "We look forward to hearing from you." Remove. Now we need to output only HTML fragment. Let's craft. Structure:
About the role
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.
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
- ... etc. For prose,