Financial Connections TechOps Integration Reliability Engineer

What you'll do

Operate, maintain, and expand banking integrations

• Become a domain expert in open banking, financial data access, and data aggregation—the systems, the partners, and the failure modes
• Own integration health end-to-end: triage degradations, diagnose root causes, coordinate with financial partners, and drive resolution with urgency
• Handle technical inquiries from internal Stripe teams and external partners, often requiring deep investigation and targeted code or configuration changes
• Build and launch new financial partner integrations using agentic tooling
• Conduct complex data analysis to investigate product performance, scope partner requirements, and surface reliability insights

Build agentic systems and automation

• Design, build, and ship LLM-powered agentic workflows that streamline and automate high-volume operational tasks
• Operate as a Human-in-the-Loop reviewer for automated processes that carry meaningful risk, applying your domain expertise where automation alone isn't sufficient
• Identify inefficient or manual processes and eliminate them through AI-powered automation, code changes, or driving complex process improvements across Stripe

Partner and scale

• Serve as a technical point of contact for financial partners—troubleshooting issues, aligning on product usage, and managing relationships with clear communication
• Provide authoritative technical context to cross-functional partners including product, partnerships, compliance, and legal
• Design and improve anomaly detection systems and observability tooling to ensure data flowing through partner and internal systems is reliable and correct

Who you are

TechOps IRE roles combine software engineering, data analysis, AI systems development, and cross-functional partner management. The ideal candidate brings experience across technical systems, data investigation, and complex project ownership—and finds genuine satisfaction in making things run reliably at scale through both human judgment and intelligent automation.

Minimum requirements

• Strong technical problem-solving skills, with the ability to develop a working understanding of complex systems through a variety of methods: reading and writing code, studying documentation and partner specifications, running debugging tools, reading logs, querying raw data, and asking precise questions of domain experts
• Experience building with AI and LLM tooling with established clear outcomes—you don't need experience with any specific framework, but you should be able to pick up new tools quickly and think clearly about where automation adds value versus where human judgment is required
• Strong SQL skills and proficiency navigating a variety of data systems to diagnose and scope issues
• Comfort with developer tools (e.g. git) and an ability to make well-scoped code changes in a large codebase
• Strong written and verbal communication skills, with the ability to frame messages appropriately for both technical and non-technical audiences
• An instinct to build solutions that increase the leverage of the people around you—not just to solve the problem in front of you, but to eliminate the class of problem

Preferred qualifications

• Knowledge of and experience with payment technologies, open banking, and financial data ecosystems
• Experience designing or operating agentic or LLM-powered workflows in a production environment
• Proficiency with Presto, Splunk, or similar data querying and log analysis tools
• Experience managing technical relationships with external partners or vendors