About the team

You'll be joining the Finance Operational Excellence team, reporting to the Finance AI Solution Architect. Our mission is to operationalize AI agents at scale for Finance, supporting the AI Strategy to transform how Finance teams work. We sit at the intersection of Finance domain expertise, data engineering, and emerging AI technologies.

We serve as Global AI Solution Architects for Finance, working with domain AI leaders and SMEs across Controllership, F&S, Treasury, Tax, Finance Operations and Facilities. Our goal is not just to build AI solutions, but to operationalize them—handing off agents to Finance teams for long-term ownership and adaptation. This means we teach while we work. Engineering partners help with complex technical work and custom tool development, while we deliver solutions using Agentic AI and other emerging AI tools.

We work within platform constraints creatively, build reusable knowledge layers, and enable Finance teams to maintain AI solutions independently. We have deep expertise in data analysis, process digitalization and applied AI. If you have a passion for technology and problem solving, and are excited about the future of AI at work, keep reading.

You'll work side-by-side with Finance, Product, and Engineering teams to build and operationalize AI-powered automation solutions that transform how Finance teams work at Stripe. 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 collaborate closely with Finance subject matter experts to understand their workflows, translate requirements into technical solutions, and iterate based on feedback. When you encounter platform limitations—which you will—you'll find creative workarounds, collaborate with Engineering to scope and test custom tools, and escalate strategically when needed. You'll establish reusable components to accelerate the portfolio of Finance AI use cases.

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.

• Build and operationalize AI agents for Finance use cases using Agentic Solutions and other automation tools, delivering end-to-end solutions from prototype to handoff
• Design reusable knowledge layers, validation patterns, and data quality frameworks to improve agent accuracy and reliability across multiple use cases

Identify agentic limitations and new possibilities; collaborate with Engineering to scope custom tools and integrations (via MCP) when capabilities are insufficient, providing requirements, testing implementations, and integrating tools into agent workflows

• Work independently to scope automation opportunities, navigate platform constraints through creative workarounds (pre-coded tools, query chaining, validation agents), and strike a balance between speed and quality to deliver impact quickly
• Enable Finance teams through training, documentation (SOPs, runbooks), and self-service tooling for minimal ongoing support
• Be the accountable technical expert with Finance SMEs across multiple organizations to understand manual processes, translate requirements into technical solutions, and iterate based on feedback
• Write and optimize SQL queries for data extraction, transformation, and validation that feed agent workflows, ensuring data quality and accuracy for Finance use cases
• Establish monitoring and observability for deployed agents, including metrics, alerting, and incident response processes to ensure reliability
• Serve as the escalation point for technical issues, diagnosing problems independently and collaborating with Engineering when solutions require deeper platform changes
• Document learnings, patterns, and best practice news bulletins for reuse across the Finance AI portfolio, contributing to organizational knowledge and scaling impact
• 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.
• 3+ years of experience in Data Analytics, Technical Operations, Business Intelligence, or similar roles
• Experience with emerging AI/LLM tools, conversational interfaces, prompt engineering, or automation platforms and RPA
• Proficiency in SQL including writing complex queries, using CTEs (common table expressions), window functions, and joins for data analysis and pipeline logic
• Experience with automation through low-code tools, scripting, workflow automation, or building custom integrations that extend platform capabilities paired with curiosity to learn evolving tools
• Track record of independently scoping and delivering technical solutions for process improvement, demonstrating self-sufficiency and ownership
• Strong analytical and investigative skills to identify root causes of data issues, debug complex problems, and resolve inconsistencies
• Understanding of development best practices such as version control, testing, code reviews, and iterative development
• Familiarity with modern data tools (Python, Databricks, ETL/ELT processes, data pipelines) and coding with AI assistance
• Experience with Model Context Protocol (MCP) or similar extensibility frameworks
• Background in Finance Operations, Financial Planning & Analysis (FP&A), Accounting, Treasury, or Payments
• Experience navigating the complexity of financial systems (accounting, reporting, reconciliation, payments, etc.) and understanding how data flows through them
• Experience working in high-growth technology companies 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 learning technical concepts, collaborating closely with Engineering teams, and using AI-assisted development tools to extend platform capabilities when needed.

• Location & Team Structure
• Location : Bangalore, India (in-office)
• Reports to : Finance AI Solution Architect

Collaboration : Work closely with Finance teams globally, Engineering partners, and the AI Foundation team