AI Engineer

AI Engineer Who We Are 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 The Solutions Architecture (SA) organization helps Stripe's most strategic customers design and validate technical solutions that drive their business forward. Within SA, our team builds the tools, workflows, and custom technical assets that make the broader SA org more effective—turning individual ingenuity into org-wide capability. We are looking for AI Engineers who are energized by working close to the business and the users we serve. You'll operate as an embedded, high-context engineer focused on the highest-leverage opportunities across the SA org—building production-quality tooling, supporting our most strategic engagements, and shipping automation that meaningfully improves how Solutions Architects work every day. What You'll Do As an AI Engineer, you'll be embedded directly with the Solutions Architecture team—building alongside them, deeply understanding their workflows, and shipping tools and automation that permanently change how they operate. Your measure of success is SA productivity: the engagements you've accelerated, the workflows you've transformed, and the tools you've built that the org adopts as default. You'll ship code daily. You'll discover where SAs lose time and build high-impact solutions. You'll take what works for one person and scale it to work for the org. And when our most strategic customer engagements need custom technical assets, you'll build those too. This is a role for someone who wants to work at the intersection of engineering and business impact—close to customers, close to revenue, and building for people you can see using your work every day. Responsibilities - Collaborate with Solutions Architects, SA leadership, Product, and Engineering to scope technical work and translate ambiguous business needs into well-defined deliverables - Evaluate and integrate AI capabilities (LLMs, agents, workflow automation) where they provide genuine leverage—not for novelty, but for measurable productivity improvement - Architect and build internal tools, agents, and automated workflows that accelerate SA and manager productivity across technical discovery, solution design, demoing, user engagements, territory/pipeline management, and product interlock - Take high-potential tools and workflows built by SAs and managers and harden them into scalable, maintainable, production-grade solutions - Identify patterns across SA workflows and proactively build solutions that address recurring friction - Build custom demo environments, PoC applications, and technical assets for Stripe's most strategic customer engagements - Document tools, architectures, and usage patterns so others can adopt and extend what you've built - Debug, extend, and maintain backend systems across a variety of codebases and infrastructure Minimum Requirements - 4+ years of experience as an engineer shipping production systems - Strong backend engineering fundamentals: you can debug a failing system, trace issues across services, and reason about data flows - Experience building and deploying AI agents, LLM-powered tools, or workflow automation beyond basic prompt engineering - Experience scoping and delivering work with minimal oversight in a fast-moving, cross-functional environment - Proficiency in at least two of: Ruby, Node.js, Python, or Next.js - Familiarity with cloud infrastructure (AWS, GCP) including deployment, monitoring, and basic DevOps - Experience building internal tools, developer platforms, or workflow automation - Demonstrated ability to work across multiple codebases and technology stacks simultaneously - Hands-on experience using AI/LLM tools in your engineering workflow—you're fluent with AI-assisted development but not dependent on it; you can reason through problems and debug without AI as a crutch - Strong written and verbal communication skills; you can translate technical decisions for non-technical stakeholders and navigate cross-functional collaboration naturally - Comfort with ambiguity—you can take a loosely-defined business problem, scope the engineering work, and ship iteratively without waiting for a perfect spec Preferred Qualifications - Experience designing systems that non-engineers can build on top of or extend themselves (e.g., platforms, low-code frameworks, template systems) - Experience in a Solutions Engineering, Sales Engineering, or GTM Engineering role—or a product engineering role where you worked cl