AI Engineer
Stripe is hiring an AI Engineer in Chicago, United States. Level rates it ; you can apply on Level.
AI in this role
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 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
Who You Are
Beyond the technical requirements, we're looking for a specific kind of engineer:
- You want to be close to the business. You're energized by seeing your work directly impact how a sales team wins a deal or how a customer succeeds.
- You're a pragmatic builder. You ship working solutions quickly, iterate based on real usage, and know when "good enough now" beats "perfect later." You'd rather show a working prototype today than present a roadmap deck next quarter.
- You're a software engineer by practice. You can architect systems, debug production issues, write clean code, and reason about tradeoffs. AI is a tool in your belt, not a substitute for engineering judgment.
- You're a pattern recognizer. When you build something that works for one person, you immediately see how it generalizes. You think in reusable systems, not one-off scripts.
- You thrive without a traditional product team structure. No PRDs landing in your lap, no dedicated PM, no sprint ceremonies. You identify the highest-leverage problem, scope the work, and ship it. You're comfortable trading on-call rotations and rigid processes for autonomy and impact.
- You're a strong communicator. You can partner with SAs who are domain experts, understand their workflows deeply enough to build great tools, and explain your technical choices to leadership.
How we rate this
AI Engineer at Stripe rates 78 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What are the limits of Gong that you've run into, and how did you work around them?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, AI agents, and Gong. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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