AI Solutions Developer
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Use - for any list of duties/requirements/benefits, and
for prose. Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it. Preserve ALL substantive information; do NOT invent or summarize away detail. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. IMPORTANT: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. Prefer a few substantive sections over many thin ones. Output ONLY the HTML fragment — no /, no markdown code fences.
We need to decide which sections to include based on content. The posting includes:
- Who we are / About Stripe (description)
- About The Team
- What you’ll do (description)
- Responsibilities (list)
- Who you are (intro)
- Minimum Requirements (list)
- You Will Also Likely Have (not Required) (list)
- Note on technical depth (prose)
- In-office expectations (prose)
- Pay and benefits (prose with salary range and benefits list)
- Additional benefits (list)
- At Stripe, we're looking for people... (maybe can be part of closing but could be considered boilerplate? It's not EEO but it's motivational; maybe keep as prose? It's not boilerplate but could be considered generic. However we need to preserve substantive information; it's not essential but could be kept. However we might drop as it's not specific to role? It's generic Stripe messaging. Might be considered boilerplate? The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. This is not exactly those, but it's generic motivational. Might be okay to keep but could be considered filler. Safer to drop? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." This is substantive? It's about company values; could be considered substantive but not role-specific. I'd keep it as a short paragraph maybe under a heading like "About Stripe" already covers mission. The final paragraph "At Stripe, we're looking for people..." is similar to earlier mission. Could be considered duplicate. I'd drop it to avoid duplication.
Also "Please find our California applicant personal information notice here." is legal boilerplate; drop.
Thus sections:
- About Stripe (maybe combine Who we are and About Stripe)
- About The Team
- What you’ll do
- Responsibilities
- Minimum Requirements
- Preferred Qualifications (You Will Also Likely Have)
- Technical Depth Note (maybe as a paragraph under a heading like "Technical Depth")
- In-office Expectations
- Pay and Benefits (including salary range and benefits list)
We need to use
for each section heading.
We need to use - for any list of duties/requirements/benefits.
We need to use
for prose.
We must not repeat job title as heading.
We must not include Pay/Schedule/Benefits sections unless posting actually states them. It does state Pay and benefits, so we include.
We must not create Schedule section if not present.
We must not create Benefits section separate if we include under Pay and benefits.
We need to preserve all substantive information.
Let's extract content.
**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**: Paragraph: "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**: list items (each sentence starts with a verb). Let's extract:
- 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**: Intro: "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**: list:
- 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—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)**: 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.
**Note on technical depth**: paragraph: "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."
**In-office expectations**: paragraph: "Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible."
**Pay and benefits**: paragraph: "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."
Then list of additional benefits: "Additional benefits for this role may include: equity, company bonus or sales commissions
for prose. Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it. Preserve ALL substantive information; do NOT invent or summarize away detail. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. IMPORTANT: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. Prefer a few substantive sections over many thin ones. Output ONLY the HTML fragment — no /, no markdown code fences. We need to decide which sections to include based on content. The posting includes: - Who we are / About Stripe (description) - About The Team - What you’ll do (description) - Responsibilities (list) - Who you are (intro) - Minimum Requirements (list) - You Will Also Likely Have (not Required) (list) - Note on technical depth (prose) - In-office expectations (prose) - Pay and benefits (prose with salary range and benefits list) - Additional benefits (list) - At Stripe, we're looking for people... (maybe can be part of closing but could be considered boilerplate? It's not EEO but it's motivational; maybe keep as prose? It's not boilerplate but could be considered generic. However we need to preserve substantive information; it's not essential but could be kept. However we might drop as it's not specific to role? It's generic Stripe messaging. Might be considered boilerplate? The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. This is not exactly those, but it's generic motivational. Might be okay to keep but could be considered filler. Safer to drop? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." This is substantive? It's about company values; could be considered substantive but not role-specific. I'd keep it as a short paragraph maybe under a heading like "About Stripe" already covers mission. The final paragraph "At Stripe, we're looking for people..." is similar to earlier mission. Could be considered duplicate. I'd drop it to avoid duplication. Also "Please find our California applicant personal information notice here." is legal boilerplate; drop. Thus sections: - About Stripe (maybe combine Who we are and About Stripe) - About The Team - What you’ll do - Responsibilities - Minimum Requirements - Preferred Qualifications (You Will Also Likely Have) - Technical Depth Note (maybe as a paragraph under a heading like "Technical Depth") - In-office Expectations - Pay and Benefits (including salary range and benefits list) We need to use
for each section heading.
We need to use - for any list of duties/requirements/benefits.
We need to use
for prose.
We must not repeat job title as heading.
We must not include Pay/Schedule/Benefits sections unless posting actually states them. It does state Pay and benefits, so we include.
We must not create Schedule section if not present.
We must not create Benefits section separate if we include under Pay and benefits.
We need to preserve all substantive information.
Let's extract content.
**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**: Paragraph: "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**: list items (each sentence starts with a verb). Let's extract:
- 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**: Intro: "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**: list:
- 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—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)**: 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.
**Note on technical depth**: paragraph: "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."
**In-office expectations**: paragraph: "Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible."
**Pay and benefits**: paragraph: "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."
Then list of additional benefits: "Additional benefits for this role may include: equity, company bonus or sales commissions
for prose. We must not repeat job title as heading. We must not include Pay/Schedule/Benefits sections unless posting actually states them. It does state Pay and benefits, so we include. We must not create Schedule section if not present. We must not create Benefits section separate if we include under Pay and benefits. We need to preserve all substantive information. Let's extract content. **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**: Paragraph: "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**: list items (each sentence starts with a verb). Let's extract: - 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**: Intro: "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**: list: - 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—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)**: 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. **Note on technical depth**: paragraph: "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." **In-office expectations**: paragraph: "Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible." **Pay and benefits**: paragraph: "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." Then list of additional benefits: "Additional benefits for this role may include: equity, company bonus or sales commissions