AI Engineer

Stripe Stripe · Fintech · United States · 1150 Solutions Architecture

AI Engineer role focused on building production-quality internal tools, agents, and automated workflows for the Solutions Architecture team at Stripe. The role emphasizes integrating AI capabilities to improve SA productivity, accelerate customer engagements, and harden existing tools into scalable solutions. Requires strong backend engineering fundamentals and experience building AI agents or LLM-powered tools.

What you'd actually do

  1. Collaborate with Solutions Architects, SA leadership, Product, and Engineering to scope technical work and translate ambiguous business needs into well-defined deliverables
  2. Evaluate and integrate AI capabilities (LLMs, agents, workflow automation) where they provide genuine leverage—not for novelty, but for measurable productivity improvement
  3. 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
  4. Take high-potential tools and workflows built by SAs and managers and harden them into scalable, maintainable, production-grade solutions
  5. Identify patterns across SA workflows and proactively build solutions that address recurring friction

Skills

Required

  • 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

Nice to have

  • 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 closely with customers or go-to-market teams
  • Familiarity with Stripe's products, APIs, or the payments/fintech domain
  • Experience integrating with third-party platforms (Salesforce, Gong, etc.)
  • Track record of building tools or systems that were adopted beyond your immediate team
  • Background in consulting, professional services, or other roles that blend technical depth with business context

What the JD emphasized

  • shipping production systems
  • building and deploying AI agents, LLM-powered tools, or workflow automation beyond basic prompt engineering
  • building internal tools, developer platforms, or workflow automation
  • Hands-on experience using AI/LLM tools in your engineering workflow

Other signals

  • building production-quality tooling
  • shipping automation
  • integrating AI capabilities (LLMs, agents, workflow automation)
  • architecting and building internal tools, agents, and automated workflows