AI Engineer
Remote • Chicago
Posted 10d ago
Job Location
Chicago
Tech Stack
Remote Work Policy
Fully remote
Categories
Applied AI Engineer
About the job
Stripe is seeking an AI Engineer to join the Solutions Architecture team. This role involves embedding directly with Solutions Architects to understand their workflows and build production-quality tools, agents, and automation that enhance their productivity. You will focus on high-leverage opportunities, transforming how the team operates by scaling individual solutions to organizational capabilities. The goal is to measurably improve SA productivity through accelerated engagements and transformed workflows, working at the intersection of engineering and business impact.
Responsibilities
- Collaborate with cross-functional teams to define technical work and translate business needs into deliverables.
- Evaluate and integrate AI capabilities like LLMs and agents for measurable productivity improvements.
- Architect and build internal tools, agents, and automated workflows to boost SA and manager productivity.
- Harden high-potential tools and workflows into scalable, production-grade solutions.
- Identify patterns in SA workflows and proactively build solutions for recurring friction.
- Build custom demo environments, PoC applications, and technical assets for strategic customer engagements.
- Document tools, architectures, and usage patterns for adoption and extension.
- Debug, extend, and maintain backend systems across various codebases and infrastructure.
Requirements
- 4+ years of experience shipping production systems as an engineer.
- Strong backend engineering fundamentals, including debugging and reasoning about data flows.
- Experience building and deploying AI agents, LLM-powered tools, or workflow automation.
- 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 and monitoring.
- Experience building internal tools, developer platforms, or workflow automation.
- Demonstrated ability to work across multiple codebases and technology stacks.
- Hands-on experience using AI/LLM tools in your engineering workflow.
- Strong written and verbal communication skills for translating technical decisions to non-technical stakeholders.
- Comfort with ambiguity and iterating on loosely-defined business problems.